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CVE Record

CVE-2026-22870: GuardDog Zip Bomb Vulnerability in safe_extract() Allows DoS

GuardDog is a CLI tool to identify malicious PyPI packages. Prior to 2.7.1, GuardDog's safe_extract() function does not validate decompressed file sizes when extracting ZIP archives (wheels, eggs), allowing attackers to cause denial of service through zip bombs. A malicious package can consume gigabytes of disk space from a few megabytes of compressed data. This vulnerability is fixed in 2.7.1.

HighCVSS 7.1Not KEV-listedUpdated
Glexia's TakeAutomated analysishigh

Security readout for executives and security teams

Plain-English summary

GuardDog versions before 2.7.1 can be forced to unpack a malicious Python package archive that expands massively on disk. This can fill storage and disrupt systems running GuardDog scans. The issue affects availability, not data confidentiality or integrity, based on the provided CVSS and description.

Executive priority

Treat as a high-priority operational resilience fix for software supply-chain scanning environments. It can interrupt security workflows by exhausting disk space, but the provided evidence does not show data theft, code execution, or active exploitation.

Technical view

CVE-2026-22870 is a CWE-409 zip bomb issue in DataDog GuardDog safe_extract(). Before 2.7.1, ZIP archive extraction for wheels or eggs did not validate decompressed file sizes. A crafted package can expand from small compressed input into gigabytes of disk usage, causing denial of service. The vendor fix is in GuardDog 2.7.1.

Likely exposure

Exposure is likely where GuardDog before 2.7.1 scans untrusted or third-party PyPI packages, especially automated CI, package vetting, or dependency intake workflows. Systems only scanning trusted internal packages have lower practical exposure, but should still update.

Exploitation context

The CVSS vector indicates network attackability with low complexity, no privileges, and user interaction required. In practice, a victim workflow must process a malicious archive. The source bundle does not indicate active exploitation, and the CVE is not listed as KEV.

Researcher notes

The key security boundary is archive extraction inside safe_extract(). The fix reference should be reviewed to understand added decompressed-size validation. Avoid assuming broader archive formats or products beyond GuardDog and ZIP-based wheels or eggs unless confirmed by vendor sources.

Mitigation direction

  • Upgrade DataDog GuardDog to version 2.7.1 or later.
  • Prioritize scanners that process untrusted PyPI packages or public submissions.
  • Review vendor advisory and commit for implementation details.
  • If immediate upgrade is delayed, check vendor guidance for supported temporary controls.

Validation and detection

  • Inventory GuardDog installations and identify versions earlier than 2.7.1.
  • Confirm CI and package analysis jobs use the updated GuardDog version.
  • Check whether GuardDog scans wheels or eggs from untrusted sources.
  • Monitor recent scanner failures or storage exhaustion during package analysis.
Prepared
Confidence
high
Sources
4

Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.

Potential ATT&CK relevance

Conservative CVE-to-ATT&CK context

These mappings and lookup hints may be relevant to the vulnerability behavior, CWE, affected product, or exposure path. Glexia-inferred context is not an official MITRE, ATT&CK, CWE, or CVE Program mapping.

ATT&CK lookup starting points

Use these exact CWE pages and searches to review the Glexia ATT&CK library from this CVE's weakness and description context.

cwe · low confidence lookup

CWE-409: Exact CWE lookup

Use the exact CWE identifier as the starting point before reviewing related ATT&CK behavior. Open the exact CWE lookup page first, then review the ATT&CK searches from that MITRE weakness context. This is a Glexia lookup hint, not an official ATT&CK mapping.

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cve · low confidence lookup

CVE-2026-22870 mapping review

Open the CVE-to-ATT&CK bridge for reviewed, inferred, or future official mappings tied to this CVE.

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Vulnerability profileCVE Program record
Severity
High
CVSS
7.1 (4.0)
Known Exploited
No
Published

Vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

Official CVE source material

CNA and ADP enrichment extracted from CVE v5

These fields come from the CVE record and ADP containers, not from Glexia's Take. They preserve time-varying source decisions such as CISA SSVC, KEV status, CVSS metrics, and provider references.

1CVSS vectors
0Timeline events
0ADP providers
3Source links

CVSS vector scores

1 official score

We collect every scored CVSS vector available in the official CNA and ADP containers. When more than one version is present, the table keeps the source vectors side by side instead of collapsing them into the highest score.

ScoreVersionSeverityVectorExploitImpactSource
7.1CVSS 4.0HighCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N——Primary CVE score

Vulnerability scoring details

Base CVSS 4.0 score

7.1High
CVSS 4.0 vector shape for CVE-2026-22870Attack VectorAttack ComplexityAttack RequirementsPrivileges RequiredUser InteractionVS ConfidentialityVS IntegrityVS AvailabilitySS ConfidentialitySS IntegritySS Availability

Vector: CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

Attack Vector
NetworkAdjacentLocalPhysical
Attack Complexity
LowHigh
Attack Requirements
NonePresent
Privileges Required
NoneLowHigh
User Interaction
NonePassiveActive
VS Confidentiality
HighLowNone
VS Integrity
HighLowNone
VS Availability
HighLowNone
SS Confidentiality
HighLowNone
SS Integrity
HighLowNone
SS Availability
HighLowNone
Affected products

Products and packages named in the record

VendorProductVersion / packageStatus
DataDogguarddog< 2.7.1Listed
Weakness

CWE details

CWE links open Glexia weakness intelligence pages with official CWE context, developer remediation guidance, and related CVE mappings.

CWE-409 · source CWE mapping

Improper Handling of Highly Compressed Data (Data Amplification)

Improper Handling of Highly Compressed Data (Data Amplification) represents a recurring weakness pattern that can create exploitable paths when design, validation, or implementation controls are missing.