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VulnerabilityPublished

CVE-2026-4745: dendibakh perf-ninja · Code Injection

Affects dendibakh perf-ninjaSource CVE Database V5

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Not known to be exploited · CVSS 10.0 Critical.

Data as of 30 Oct 2026, 11:52 UTC

CVSS 4.0 base score
10.0Critical
How severe the flaw is on the 0–10 CVSS scale.

Contested

Critical score, yet low EPSS after six months
EPSS
0.2% chance of exploitation in 30 days – higher than 19% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H/E:A/S:N/AU:Y/R:U/V:D/RE:L/U:Amber

Exploitation evidence

  1. Disclosed: evidence found.

    CVE published 24 Mar 2026

  2. Detectable: no evidence on record.

    No public nuclei template indexed

  3. Weaponized: no evidence on record.

    No public exploit code indexed in Metasploit or Exploit-DB

  4. Exploited in the wild: no evidence on record.

    Not in CISA KEV and no source reports exploitation

  5. Observed by OffSeq Mirage: no evidence on record.

    No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 30 Oct 2026.

What to do

Affected software

ProductAffectedFixed in
dendibakhperf-ninjaAffected
  • =0
Fixed in–
GitHubdendibakh/perf-ninjapkg:github/dendibakh/perf-ninjaOther threatsAffected
  • =0
Fixed in–
GitHubperf-ninjapkg:github/perf-ninjaOther threatsAffected
  • =0
Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

  1. Immediately restrict network access to systems running perf-ninja, especially the labs/misc/pgo/lua modules, limiting exposure to trusted internal networks only.
  2. Implement strict input validation and sanitization for any user-supplied data processed by perf-ninja to prevent injection of malicious code.
  3. Employ application-level sandboxing or containerization to isolate perf-ninja processes, minimizing potential damage from exploitation.
  4. Monitor logs and network traffic for unusual activity indicative of code injection attempts or unauthorized execution.
  5. Conduct thorough vulnerability scanning and penetration testing focused on perf-ninja deployments to identify exposure.
  6. Coordinate with the dendibakh vendor or community for timely patch releases and apply updates as soon as they become available.
  7. Educate development and operations teams about the risks of this vulnerability and enforce the principle of least privilege for users interacting with perf-ninja.
  8. Consider temporary disabling or replacing perf-ninja with alternative tools until a secure version is released.

Description

Improper Control of Generation of Code ('Code Injection') vulnerability in dendibakh perf-ninja (labs/misc/pgo/lua modules). This vulnerability is associated with program files ldo.C. This issue affects perf-ninja.

References

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