Code Injection in PraisonAI (CVE-2026-62176)
Summary
Code injection in PraisonAI (CVE-2026-62176). Successful exploitation can lead to full system takeover. Exploitable via agents_file. Mitigation: upgrade to 4.6.78 or later.
Original description
The description as published by the source.
Summary
The deploy/api.py module generates Python server code by directly interpolating the agents_file parameter into an f-string that is then written to a file and executed via subprocess.Popen(). An attacker who controls the agents_file value (via CLI argument, configuration, or upstream API) can inject arbitrary Python code.
Details
src/praisonai/praisonai/deploy/api.py (line 80):
code = f'''...
praisonai = PraisonAI(agent_file="{agents_file}")
...
"agent_file": "{agents_file}"
...'''
The generated code is then executed (line 190):
subprocess.Popen(['python', server_file])
agents_file is never sanitized or validated. A malicious value breaks out of the string context:
agents_file = '"); import os; os.system("id"); #'
# Generated code becomes:
# praisonai = PraisonAI(agent_file=""); import os; os.system("id"); #")
The same pattern exists in deploy/docker.py (line 33) for Dockerfile generation.
PoC
# The injection:
agents_file = '"); import os; os.system("id"); #'
# What the generated code looks like:
template = f'praisonai = PraisonAI(agent_file="{agents_file}")'
print(template)
# Output: praisonai = PraisonAI(agent_file=""); import os; os.system("id"); #")
Impact
- Arbitrary code execution on the machine running the deploy command
- Supply chain risk if
agents_filecomes from a configuration file or CI/CD pipeline
Source: GitHub Security Advisories (Global) NVD GitHub Advisory
Auto-generated summary
Assembled by SecPulse from the source data (CVSS, CWE, affected versions) using templates — no AI involved. Check the original description and references below for exact details.
A vulnerability tracked as CVE-2026-62176 has been found in PraisonAI.
Attackers can target a specific entry point like agents_file over the network to misuse the product.
Successful exploitation can lead to full system takeover. CVSS score: 9.1/10.
What to do: upgrade PraisonAI to 4.6.78 or later.
If unsure, ask your IT team or search "PraisonAI CVE-2026-62176" on the vendor's site.
CVE-2026-62176 (PraisonAI) — CWE-94 / CVSS v3 9.1
Attack vector: remote (network-reachable) / no user interaction
Attack surface: agents_file
Patched: 4.6.78 — apply immediately
Plan: 1) Audit SBOM/dependencies, 2) Stage→prod upgrade, 3) Add WAF/proxy monitoring on affected endpoints, 4) Hunt IOCs in logs.
Refs: see the GHSA / vendor advisory / patched release linked on this page.
Arbitrary code execution (CWE-94) exists in PraisonAI. Attackers reach the vulnerable code path via agents_file.
Check the vendor advisory for the affected versions of PraisonAI. Attack surface: agents_file.
Severity: Critical (CVSS 9.1/10). Successful exploitation can lead to full system takeover.
Update to 4.6.78.
Until the patch is applied: disable the affected feature, apply WAF rules, or restrict access via network ACLs.
Search webserver/proxy logs for unusual request patterns matching this CVE's known IOCs. Run grep -r 'PraisonAI' . against your dependency files (package-lock.json, requirements.txt, go.sum) to find affected services.
Response actions
Concrete steps and command examples for SOC/SRE teams to execute in order
-
1Identify exposure identify
grep -r 'PraisonAI' . | grep -v node_modulesリポジトリと本番環境の依存ファイル (package-lock.json / requirements.txt / go.sum / Gemfile.lock 等) で
PraisonAIを grep し、稼働しているサービス・バージョンを把握する。 -
2Apply patch patch
Upgrade PraisonAI to 4.6.78ステージング環境で 4.6.78 に上げて回帰テスト → 本番反映。回帰テストはアプリの主要ハッピーパスを含めること。
-
3Post-deployment verification verify
Confirm patched version is live in productionパッチ適用後、ステージングで PoC または同等の悪用パターンを再現して脆弱性が閉じたことを確認。本番ではアクセスログ・WAF でアラート再発が無いか継続監視。
Affected packages
References
- web github.com
- web github.com