CVE-2026-56078

PraisonAI before 1.5.115 contains a path traversal vulnerability in MultiAgentMonitor that fails to sanitize agent IDs when building file paths. Attackers can include traversal sequences like ../ in agent IDs to read, write, or overwrite arbitrary files, enabling sensitive disclosure, denial of service, or code execution.

PraisonAI before 1.5.115 contains a path traversal vulnerability in MultiAgentMonitor that fails to sanitize agent IDs when building file paths. Attackers can include traversal sequences like ../ in agent IDs to read, write, or overwrite arbitrary files, enabling sensitive disclosure, denial of service, or code execution.

Summary

The MultiAgentLedger and MultiAgentMonitor components in the provided code exhibit vulnerabilities that can lead to context leakage and arbitrary file operations. Specifically:

1. Memory State Leakage via Agent ID Collision: The MultiAgentLedger uses a dictionary to store ledgers by agent ID without enforcing uniqueness. This allows agents with the same ID to share ledger instances, leading to potential leakage of sensitive context data.
2. Path Traversal in MultiAgentMonitor: The MultiAgentMonitor constructs file paths by concatenating the base_path and agent ID without sanitization. This allows an attacker to escape the intended directory using path traversal sequences (e.g., ../), potentially leading to arbitrary file read/write.

Details

Vulnerability 1: Memory State Leakage

• File: examples/context/12_multi_agent_context.py:68
• Description: The MultiAgentLedger class uses a dictionary (self.ledgers) to store ledger instances keyed by agent ID. The get_agent_ledger method creates a new ledger only if the agent ID is not present. If two agents are registered with the same ID, they will share the same ledger instance. This violates the isolation policy and can lead to leakage of sensitive context data (system prompts, conversation history) between agents.
• Exploitability: An attacker can register an agent with the same ID as a victim agent to gain access to their ledger. This is particularly dangerous in multi-tenant systems where agents may handle sensitive user data.

Vulnerability 2: Path Traversal

• File: examples/context/12_multi_agent_context.py:106
• Description: The MultiAgentMonitor class constructs file paths for agent monitors by directly concatenating the base_path and agent ID. Since the agent ID is not sanitized, an attacker can provide an ID containing path traversal sequences (e.g., ../../malicious). This can result in files being created or read outside the intended directory (base_path).
• Exploitability: An attacker can create an agent with a malicious ID (e.g., ../../etc/passwd) to write or read arbitrary files on the system, potentially leading to information disclosure or file corruption.

PoC

Memory State Leakage

multi_ledger = MultiAgentLedger()

# Victim agent (user1) registers and tracks sensitive data
victim_ledger = multi_ledger.get_agent_ledger('user1_agent')
victim_ledger.track_system_prompt("Sensitive system prompt")
victim_ledger.track_history([{"role": "user", "content": "Secret data"}])

# Attacker registers with the same ID
attacker_ledger = multi_ledger.get_agent_ledger('user1_agent')

# Attacker now has access to victim's ledger
print(attacker_ledger.get_ledger().system_prompt)  # Outputs: "Sensitive system prompt"
print(attacker_ledger.get_ledger().history)        # Outputs: [{'role': 'user', 'content': 'Secret data'}]

Path Traversal

with tempfile.TemporaryDirectory() as tmpdir:
    multi_monitor = MultiAgentMonitor(base_path=tmpdir)
    
    # Create agent with malicious ID
    malicious_id = '../../malicious'
    monitor = multi_monitor.get_agent_monitor(malicious_id)
    
    # The monitor file is created outside the intended base_path
    # Example: if tmpdir is '/tmp/safe_dir', the actual path might be '/tmp/malicious'
    print(monitor.path)  # Outputs: '/tmp/malicious' (or equivalent)

Impact

• Memory State Leakage: This vulnerability can lead to unauthorized access to sensitive agent context, including system prompts and conversation history. In a multi-tenant system, this could result in cross-user data leakage.
• Path Traversal: An attacker can read or write arbitrary files on the system, potentially leading to information disclosure, denial of service (by overwriting critical files), or remote code execution (if executable files are overwritten).

Recommended Fix

For Memory State Leakage

• Enforce unique agent IDs at the application…

Duplicate Advisory

This advisory has been withdrawn because it is a duplicate of GHSA-766v-q9x3-g744. This link is maintained to preserve external references.

Original Description

PraisonAI before 1.5.115 contains a path traversal vulnerability in MultiAgentMonitor that fails to sanitize agent IDs when building file paths. Attackers can include traversal sequences like ../ in agent IDs to read, write, or overwrite arbitrary files, enabling sensitive disclosure, denial of service, or code execution.

PraisonAI before 1.5.115 contains a path traversal vulnerability in MultiAgentMonitor that fails to sanitize agent IDs when building file paths. Attackers can include traversal sequences like ../ in agent IDs to read, write, or overwrite arbitrary files, enabling sensitive disclosure, denial of service, or code execution.

Summary

The MultiAgentLedger and MultiAgentMonitor components in the provided code exhibit vulnerabilities that can lead to context leakage and arbitrary file operations. Specifically:

1. Memory State Leakage via Agent ID Collision: The MultiAgentLedger uses a dictionary to store ledgers by agent ID without enforcing uniqueness. This allows agents with the same ID to share ledger instances, leading to potential leakage of sensitive context data.
2. Path Traversal in MultiAgentMonitor: The MultiAgentMonitor constructs file paths by concatenating the base_path and agent ID without sanitization. This allows an attacker to escape the intended directory using path traversal sequences (e.g., ../), potentially leading to arbitrary file read/write.

Details

Vulnerability 1: Memory State Leakage

• File: examples/context/12_multi_agent_context.py:68
• Description: The MultiAgentLedger class uses a dictionary (self.ledgers) to store ledger instances keyed by agent ID. The get_agent_ledger method creates a new ledger only if the agent ID is not present. If two agents are registered with the same ID, they will share the same ledger instance. This violates the isolation policy and can lead to leakage of sensitive context data (system prompts, conversation history) between agents.
• Exploitability: An attacker can register an agent with the same ID as a victim agent to gain access to their ledger. This is particularly dangerous in multi-tenant systems where agents may handle sensitive user data.

Vulnerability 2: Path Traversal

• File: examples/context/12_multi_agent_context.py:106
• Description: The MultiAgentMonitor class constructs file paths for agent monitors by directly concatenating the base_path and agent ID. Since the agent ID is not sanitized, an attacker can provide an ID containing path traversal sequences (e.g., ../../malicious). This can result in files being created or read outside the intended directory (base_path).
• Exploitability: An attacker can create an agent with a malicious ID (e.g., ../../etc/passwd) to write or read arbitrary files on the system, potentially leading to information disclosure or file corruption.

PoC

Memory State Leakage

multi_ledger = MultiAgentLedger()

# Victim agent (user1) registers and tracks sensitive data
victim_ledger = multi_ledger.get_agent_ledger('user1_agent')
victim_ledger.track_system_prompt("Sensitive system prompt")
victim_ledger.track_history([{"role": "user", "content": "Secret data"}])

# Attacker registers with the same ID
attacker_ledger = multi_ledger.get_agent_ledger('user1_agent')

# Attacker now has access to victim's ledger
print(attacker_ledger.get_ledger().system_prompt)  # Outputs: "Sensitive system prompt"
print(attacker_ledger.get_ledger().history)        # Outputs: [{'role': 'user', 'content': 'Secret data'}]

Path Traversal

with tempfile.TemporaryDirectory() as tmpdir:
    multi_monitor = MultiAgentMonitor(base_path=tmpdir)
    
    # Create agent with malicious ID
    malicious_id = '../../malicious'
    monitor = multi_monitor.get_agent_monitor(malicious_id)
    
    # The monitor file is created outside the intended base_path
    # Example: if tmpdir is '/tmp/safe_dir', the actual path might be '/tmp/malicious'
    print(monitor.path)  # Outputs: '/tmp/malicious' (or equivalent)

Impact

• Memory State Leakage: This vulnerability can lead to unauthorized access to sensitive agent context, including system prompts and conversation history. In a multi-tenant system, this could result in cross-user data leakage.
• Path Traversal: An attacker can read or write arbitrary files on the system, potentially leading to information disclosure, denial of service (by overwriting critical files), or remote code execution (if executable files are overwritten).

Recommended Fix

For Memory State Leakage

• Enforce unique agent IDs at the application…

Duplicate Advisory

This advisory has been withdrawn because it is a duplicate of GHSA-766v-q9x3-g744. This link is maintained to preserve external references.

Original Description

PraisonAI before 1.5.115 contains a path traversal vulnerability in MultiAgentMonitor that fails to sanitize agent IDs when building file paths. Attackers can include traversal sequences like ../ in agent IDs to read, write, or overwrite arbitrary files, enabling sensitive disclosure, denial of service, or code execution.

Summary

The MultiAgentLedger and MultiAgentMonitor components in the provided code exhibit vulnerabilities that can lead to context leakage and arbitrary file operations. Specifically:

1. Memory State Leakage via Agent ID Collision: The MultiAgentLedger uses a dictionary to store ledgers by agent ID without enforcing uniqueness. This allows agents with the same ID to share ledger instances, leading to potential leakage of sensitive context data.
2. Path Traversal in MultiAgentMonitor: The MultiAgentMonitor constructs file paths by concatenating the base_path and agent ID without sanitization. This allows an attacker to escape the intended directory using path traversal sequences (e.g., ../), potentially leading to arbitrary file read/write.

Details

Vulnerability 1: Memory State Leakage

• File: examples/context/12_multi_agent_context.py:68
• Description: The MultiAgentLedger class uses a dictionary (self.ledgers) to store ledger instances keyed by agent ID. The get_agent_ledger method creates a new ledger only if the agent ID is not present. If two agents are registered with the same ID, they will share the same ledger instance. This violates the isolation policy and can lead to leakage of sensitive context data (system prompts, conversation history) between agents.
• Exploitability: An attacker can register an agent with the same ID as a victim agent to gain access to their ledger. This is particularly dangerous in multi-tenant systems where agents may handle sensitive user data.

Vulnerability 2: Path Traversal

• File: examples/context/12_multi_agent_context.py:106
• Description: The MultiAgentMonitor class constructs file paths for agent monitors by directly concatenating the base_path and agent ID. Since the agent ID is not sanitized, an attacker can provide an ID containing path traversal sequences (e.g., ../../malicious). This can result in files being created or read outside the intended directory (base_path).
• Exploitability: An attacker can create an agent with a malicious ID (e.g., ../../etc/passwd) to write or read arbitrary files on the system, potentially leading to information disclosure or file corruption.

PoC

Memory State Leakage

multi_ledger = MultiAgentLedger()

# Victim agent (user1) registers and tracks sensitive data
victim_ledger = multi_ledger.get_agent_ledger('user1_agent')
victim_ledger.track_system_prompt("Sensitive system prompt")
victim_ledger.track_history([{"role": "user", "content": "Secret data"}])

# Attacker registers with the same ID
attacker_ledger = multi_ledger.get_agent_ledger('user1_agent')

# Attacker now has access to victim's ledger
print(attacker_ledger.get_ledger().system_prompt)  # Outputs: "Sensitive system prompt"
print(attacker_ledger.get_ledger().history)        # Outputs: [{'role': 'user', 'content': 'Secret data'}]

Path Traversal

with tempfile.TemporaryDirectory() as tmpdir:
    multi_monitor = MultiAgentMonitor(base_path=tmpdir)
    
    # Create agent with malicious ID
    malicious_id = '../../malicious'
    monitor = multi_monitor.get_agent_monitor(malicious_id)
    
    # The monitor file is created outside the intended base_path
    # Example: if tmpdir is '/tmp/safe_dir', the actual path might be '/tmp/malicious'
    print(monitor.path)  # Outputs: '/tmp/malicious' (or equivalent)

Impact

• Memory State Leakage: This vulnerability can lead to unauthorized access to sensitive agent context, including system prompts and conversation history. In a multi-tenant system, this could result in cross-user data leakage.
• Path Traversal: An attacker can read or write arbitrary files on the system, potentially leading to information disclosure, denial of service (by overwriting critical files), or remote code execution (if executable files are overwritten).

Recommended Fix

For Memory State Leakage

• Enforce unique agent IDs at the application…