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Overview

com.fasterxml.jackson.core:jackson-core is a Core Jackson abstractions, basic JSON streaming API implementation

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the PATTERN_FLOAT regex of NumberInput, reached through looksLikeValidNumber(), where adjacent quantifiers over the same character class ([0-9]*, then an optional [.], then [0-9]+) carry no possessive quantifiers or atomic grouping, so the engine explores every split point between digit groups on non-matching input. An attacker can pin a request-handling thread and exhaust the worker pool with concurrent requests by supplying a long numeric-looking string that fails to match, since match cost is quadratic in input length, with 160,000 characters costing 74.4 seconds in a single call. This requires the application to reach looksLikeValidNumber() with attacker-controlled strings, which is the default path when jackson-databind coerces a String field to a number, and the input is bounded only by StreamReadConstraints.maxStringLength at 20,000,000 rather than by maxNumberLength at 1,000.

Workaround

This vulnerability can be avoided by lowering StreamReadConstraints.maxStringLength toward the string length the application actually needs, which caps the input this quadratic path can be handed, since it is that limit and not maxNumberLength that governs here.

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 com.fasterxml.jackson.core:jackson-core to version 2.18.11, 2.21.7, 2.22.3 or higher.

References

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

Overview

com.fasterxml.jackson.core:jackson-databind is a library which contains the general-purpose data-binding functionality and tree-model for Jackson Data Processor.

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling in the _findDeserializer() method of TypeDeserializerBase, which caches every unknown type ID as a distinct key in the _deserializers map even when all of them resolve to the same defaultImpl fallback. An attacker can grow that cache without bound for the lifetime of the process, exhausting memory over time, by submitting a stream of novel type identifiers. This requires the application to use name-based polymorphism through @JsonTypeInfo(use = Id.NAME, defaultImpl = ...), to accept attacker-controlled type identifiers, and to reuse the mapper instance across requests.

Remediation

Upgrade com.fasterxml.jackson.core:jackson-databind to version 2.18.11, 2.21.7, 2.22.3 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Issue

Overview

Affected versions of this package are vulnerable to Regular Expression Denial of Service (ReDoS) in the PATTERN_FLOAT regex of NumberInput, reached through looksLikeValidNumber(), where adjacent quantifiers over the same character class ([0-9]*, then an optional [.], then [0-9]+) carry no possessive quantifiers or atomic grouping, so the engine explores every split point between digit groups on non-matching input. An attacker can pin a request-handling thread and exhaust the worker pool with concurrent requests by supplying a long numeric-looking string that fails to match, since match cost is quadratic in input length, with 160,000 characters costing 74.4 seconds in a single call. This requires the application to reach looksLikeValidNumber() with attacker-controlled strings, which is the default path when jackson-databind coerces a String field to a number, and the input is bounded only by StreamReadConstraints.maxStringLength at 20,000,000 rather than by maxNumberLength at 1,000.

Workaround

This vulnerability can be avoided by lowering StreamReadConstraints.maxStringLength toward the string length the application actually needs, which caps the input this quadratic path can be handed, since it is that limit and not maxNumberLength that governs here.

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 tools.jackson.core:jackson-core to version 3.1.7, 3.2.2 or higher.

References

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

Overview

Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling in the _findDeserializer() method of TypeDeserializerBase, which caches every unknown type ID as a distinct key in the _deserializers map even when all of them resolve to the same defaultImpl fallback. An attacker can grow that cache without bound for the lifetime of the process, exhausting memory over time, by submitting a stream of novel type identifiers. This requires the application to use name-based polymorphism through @JsonTypeInfo(use = Id.NAME, defaultImpl = ...), to accept attacker-controlled type identifiers, and to reuse the mapper instance across requests.

Remediation

Upgrade tools.jackson.core:jackson-databind to version 3.1.7, 3.2.3 or higher.

References

• GitHub Advisory
• GitHub Commit
• GitHub Issue

Overview

Affected versions of this package are vulnerable to Use of Externally-Controlled Input to Select Classes or Code ('Unsafe Reflection') through NioPathDeserializer in src/main/java/com/fasterxml/jackson/databind/ext/NioPathDeserializer.java. An attacker can force readValue() to resolve an attacker-controlled java.nio.file.Path URI by supplying a non-file scheme such as jar:, http:, s3:, or a custom provider scheme in untrusted JSON. That input reaches new URI(value) and then Path.of(uri), which falls back to ServiceLoader<FileSystemProvider> resolution and can invoke a matching provider’s getPath(uri) during deserialization. The result is unintended provider loading and provider-driven path handling inside the application, which can trigger denial of service or other side effects depending on what FileSystemProvider implementations are present on the classpath.

Remediation

Upgrade tools.jackson.core:jackson-databind to version 3.1.6, 3.2.2 or higher.

References

• GitHub Commit
• GitHub Commit
• GitHub Commit
• GitHub PR
• Maintainer's Advisory

Overview

Affected versions of this package are vulnerable to Deserialization of Untrusted Data in the isSafeSubType() method of DefaultBaseTypeLimitingValidator, whose denylist of unsafe base types omits java.lang.Comparable, so the method returns true for any subtype resolved under a Comparable base. An attacker can trigger instantiation of arbitrary classes that implement Comparable, such as java.io.File to reach path-traversal primitives, by sending JSON with attacker-controlled type identifiers. This requires the application to use a bare @JsonTypeInfo with the default validator and no explicit PolymorphicTypeValidator, and a property or class whose declared base type is Comparable.

Workaround

This vulnerability can be avoided by configuring an explicit restrictive PolymorphicTypeValidator, such as a BasicPolymorphicTypeValidator allowlist passed to activateDefaultTyping(), instead of relying on the default validator.

Note: The discoverer of this vulnerability reports that "I have not identified a class implementing Comparable that yields code execution purely through deserialization".

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 tools.jackson.core:jackson-databind to version 3.1.6, 3.2.2 or higher.

References

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

Overview

ch.qos.logback:logback-classic is a reliable, generic, fast and flexible logging library for Java.

Affected versions of this package are vulnerable to Directory Traversal in MDCBasedDiscriminator, used by SiftingAppender, which takes an MDC value as the discriminating key without removing path separators, so the value reaches the nested FileAppender path unsanitized. An attacker can direct log output to a file outside the intended directory by supplying an MDC value containing / or \ path segments. This requires a configuration whose SiftingAppender discriminates on MDC and whose nested FileAppender interpolates the discriminating key into its file path, with that MDC value populated from attacker-influenced input.

Note: This is a bypass of the fix for the vulnerability described in CVE-2025-11226.

Details

A Directory Traversal attack (also known as path traversal) aims to access files and directories that are stored outside the intended folder. By manipulating files with "dot-dot-slash (../)" sequences and its variations, or by using absolute file paths, it may be possible to access arbitrary files and directories stored on file system, including application source code, configuration, and other critical system files.

Directory Traversal vulnerabilities can be generally divided into two types:

• Information Disclosure: Allows the attacker to gain information about the folder structure or read the contents of sensitive files on the system.

st is a module for serving static files on web pages, and contains a vulnerability of this type. In our example, we will serve files from the public route.

If an attacker requests the following URL from our server, it will in turn leak the sensitive private key of the root user.

curl http://localhost:8080/public/%2e%2e/%2e%2e/%2e%2e/%2e%2e/%2e%2e/root/.ssh/id_rsa

Note %2e is the URL encoded version of . (dot).

• Writing arbitrary files: Allows the attacker to create or replace existing files. This type of vulnerability is also known as Zip-Slip.

One way to achieve this is by using a malicious zip archive that holds path traversal filenames. When each filename in the zip archive gets concatenated to the target extraction folder, without validation, the final path ends up outside of the target folder. If an executable or a configuration file is overwritten with a file containing malicious code, the problem can turn into an arbitrary code execution issue quite easily.

The following is an example of a zip archive with one benign file and one malicious file. Extracting the malicious file will result in traversing out of the target folder, ending up in /root/.ssh/ overwriting the authorized_keys file:

2018-04-15 22:04:29 .....           19           19  good.txt
2018-04-15 22:04:42 .....           20           20  ../../../../../../root/.ssh/authorized_keys

Remediation

Upgrade ch.qos.logback:logback-classic to version 1.6.3 or higher.

References

• GitHub Commit
• Release Notes

Overview

org.apache.tomcat.embed:tomcat-embed-core is a Core Tomcat implementation.

Affected versions of this package are vulnerable to Insufficient Session Expiration due to the improper termination of WebSocket sessions when the associated HTTP session ends. An attacker can maintain access to resources beyond the intended session duration by establishing a WebSocket connection under an authenticated HTTP session and continuing to interact through the WebSocket after the HTTP session has expired.

Note: This issue was fixed in Apache Tomcat 10.1.58 but the release vote for the 10.1.58 release candidate did not pass. Therefore, although users must download 10.1.59 to obtain a version that includes a fix for this issue, version 10.1.58 is not included in the list of affected versions.

Remediation

Upgrade org.apache.tomcat.embed:tomcat-embed-core to version 9.0.121, 10.1.59, 11.0.25 or higher.

References

• Apache Mailing List
• GitHub Commit

Overview

Affected versions of this package are vulnerable to Insufficient Session Expiration due to the improper termination of WebSocket sessions when the associated HTTP session ends. An attacker can maintain access to resources beyond the intended session duration by establishing a WebSocket connection under an authenticated HTTP session and continuing to interact through the WebSocket after the HTTP session has expired.

Note: This issue was fixed in Apache Tomcat 10.1.58 but the release vote for the 10.1.58 release candidate did not pass. Therefore, although users must download 10.1.59 to obtain a version that includes a fix for this issue, version 10.1.58 is not included in the list of affected versions.

Remediation

Upgrade org.apache.tomcat.embed:tomcat-embed-websocket to version 9.0.121, 10.1.59, 11.0.25 or higher.

References

• Apache Mailing List
• GitHub Commit