{
  "affected": [
    {
      "affectedData": [
        {
          "defaultStatus": "unaffected",
          "product": "PraisonAI",
          "vendor": "PraisonAI",
          "versions": [
            {
              "lessThan": "1.5.128",
              "status": "affected",
              "version": "0",
              "versionType": "semver"
            },
            {
              "status": "unaffected",
              "version": "1.5.128",
              "versionType": "semver"
            }
          ]
        }
      ],
      "source": "disclosure@vulncheck.com"
    }
  ],
  "cveTags": [],
  "descriptions": [
    {
      "lang": "en",
      "value": "PraisonAI before 1.5.128 caches tool approval decisions by tool name only, not by invocation arguments, allowing subsequent execute_command calls to bypass approval prompts. Attackers can exploit this by obtaining initial approval for a benign command, then silently exfiltrate API keys and credentials via subsequent shell commands without user consent."
    }
  ],
  "id": "CVE-2026-56074",
  "lastModified": "2026-06-22T18:36:28.807",
  "metrics": {
    "cvssMetricV31": [
      {
        "cvssData": {
          "attackComplexity": "LOW",
          "attackVector": "LOCAL",
          "availabilityImpact": "NONE",
          "baseScore": 5.5,
          "baseSeverity": "MEDIUM",
          "confidentialityImpact": "HIGH",
          "integrityImpact": "NONE",
          "privilegesRequired": "NONE",
          "scope": "UNCHANGED",
          "userInteraction": "REQUIRED",
          "vectorString": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
          "version": "3.1"
        },
        "exploitabilityScore": 1.8,
        "impactScore": 3.6,
        "source": "disclosure@vulncheck.com",
        "type": "Secondary"
      }
    ],
    "cvssMetricV40": [
      {
        "cvssData": {
          "Automatable": "NOT_DEFINED",
          "Recovery": "NOT_DEFINED",
          "Safety": "NOT_DEFINED",
          "attackComplexity": "LOW",
          "attackRequirements": "NONE",
          "attackVector": "LOCAL",
          "availabilityRequirement": "NOT_DEFINED",
          "baseScore": 6.8,
          "baseSeverity": "MEDIUM",
          "confidentialityRequirement": "NOT_DEFINED",
          "exploitMaturity": "NOT_DEFINED",
          "integrityRequirement": "NOT_DEFINED",
          "modifiedAttackComplexity": "NOT_DEFINED",
          "modifiedAttackRequirements": "NOT_DEFINED",
          "modifiedAttackVector": "NOT_DEFINED",
          "modifiedPrivilegesRequired": "NOT_DEFINED",
          "modifiedSubAvailabilityImpact": "NOT_DEFINED",
          "modifiedSubConfidentialityImpact": "NOT_DEFINED",
          "modifiedSubIntegrityImpact": "NOT_DEFINED",
          "modifiedUserInteraction": "NOT_DEFINED",
          "modifiedVulnAvailabilityImpact": "NOT_DEFINED",
          "modifiedVulnConfidentialityImpact": "NOT_DEFINED",
          "modifiedVulnIntegrityImpact": "NOT_DEFINED",
          "privilegesRequired": "NONE",
          "providerUrgency": "NOT_DEFINED",
          "subAvailabilityImpact": "NONE",
          "subConfidentialityImpact": "NONE",
          "subIntegrityImpact": "NONE",
          "userInteraction": "PASSIVE",
          "valueDensity": "NOT_DEFINED",
          "vectorString": "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:P/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
          "version": "4.0",
          "vulnAvailabilityImpact": "NONE",
          "vulnConfidentialityImpact": "HIGH",
          "vulnIntegrityImpact": "NONE",
          "vulnerabilityResponseEffort": "NOT_DEFINED"
        },
        "source": "disclosure@vulncheck.com",
        "type": "Secondary"
      }
    ],
    "ssvcV203": [
      {
        "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
        "ssvcData": {
          "id": "CVE-2026-56074",
          "options": [
            {
              "exploitation": "poc"
            },
            {
              "automatable": "no"
            },
            {
              "technicalImpact": "partial"
            }
          ],
          "role": "CISA Coordinator",
          "timestamp": "2026-06-22T12:44:29.875373Z",
          "version": "2.0.3"
        }
      }
    ]
  },
  "published": "2026-06-18T23:16:19.213",
  "references": [
    {
      "source": "disclosure@vulncheck.com",
      "url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-ffp3-3562-8cv3"
    },
    {
      "source": "disclosure@vulncheck.com",
      "url": "https://www.vulncheck.com/advisories/praisonai-tool-approval-cache-bypass-via-coarse-grained-caching"
    },
    {
      "source": "134c704f-9b21-4f2e-91b3-4a467353bcc0",
      "url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-ffp3-3562-8cv3"
    }
  ],
  "sourceIdentifier": "disclosure@vulncheck.com",
  "vulnStatus": "Deferred",
  "weaknesses": [
    {
      "description": [
        {
          "lang": "en",
          "value": "CWE-863"
        }
      ],
      "source": "disclosure@vulncheck.com",
      "type": "Secondary"
    }
  ]
}

{
  "affected": [
    {
      "package": {
        "ecosystem": "PyPI",
        "name": "praisonaiagents"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            },
            {
              "fixed": "4.5.128"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [
    "CVE-2026-56074"
  ],
  "database_specific": {
    "cwe_ids": [
      "CWE-863"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-04-10T19:28:38Z",
    "nvd_published_at": null,
    "severity": "MODERATE"
  },
  "details": "## Summary\n\nThe approval system in PraisonAI Agents caches tool approval decisions by tool name only, not by invocation arguments. Once a user approves `execute_command` for any command (e.g., `ls -la`), all subsequent `execute_command` calls in that execution context bypass the approval prompt entirely. Combined with `os.environ.copy()` passing all process environment variables to subprocesses, this allows an LLM agent (potentially via prompt injection) to silently exfiltrate API keys and credentials without further user consent.\n\n## Details\n\nThe `require_approval` decorator in `src/praisonai-agents/praisonaiagents/approval/__init__.py:176-178` checks approval status by tool name only:\n\n```python\n@wraps(func)\ndef wrapper(*args, **kwargs):\n    if is_already_approved(tool_name):   # line 177 \u2014 checks only tool_name\n        return func(*args, **kwargs)     # line 178 \u2014 bypasses ALL approval\n```\n\nThe `mark_approved` function in `registry.py:144-147` stores only the tool name string:\n\n```python\ndef mark_approved(self, tool_name: str) -\u003e None:\n    approved = self._approved_context.get(set())\n    approved.add(tool_name)              # stores \"execute_command\", not args\n    self._approved_context.set(approved)\n```\n\nThe approval context is never cleared during agent execution \u2014 `clear_approved()` exists (`registry.py:152`) but is never called in the agent\u0027s tool execution path (`agent/tool_execution.py`).\n\nMeanwhile, the `ConsoleBackend` UI at `backends.py:95-96` misleads the user:\n\n```python\nreturn Confirm.ask(\n    f\"Do you want to execute this {request.risk_level} risk tool?\",\n    # \"this\" implies per-invocation approval\n)\n```\n\nThe UI displays the specific command arguments (lines 81-85), creating a reasonable expectation that the user is approving only that specific invocation.\n\nAdditionally, `shell_tools.py:77` passes the full process environment to every subprocess:\n\n```python\nprocess_env = os.environ.copy()  # includes OPENAI_API_KEY, etc.\n```\n\nThere is no command filtering, blocklist, or environment variable sanitization in the shell tools module.\n\n## PoC\n\n```python\nfrom praisonaiagents import Agent\nfrom praisonaiagents.tools.shell_tools import execute_command\n\n# Step 1: Create agent with shell tool\nagent = Agent(\n    name=\"worker\",\n    instructions=\"You are a helpful assistant.\",\n    tools=[execute_command]\n)\n\n# Step 2: Agent requests benign command \u2014 user sees Rich panel:\n#   Function: execute_command\n#   Risk Level: CRITICAL\n#   Arguments:\n#     command: ls -la\n#   \"Do you want to execute this critical risk tool?\" [y/N]\n# User approves \u2192 mark_approved(\"execute_command\") is called\n\n# Step 3: All subsequent execute_command calls bypass approval silently:\n# execute_command(command=\"env\")\n#   \u2192 returns ALL environment variables (OPENAI_API_KEY, AWS_SECRET_ACCESS_KEY, etc.)\n#   \u2192 NO approval prompt shown\n\n# Step 4: Targeted extraction also bypasses approval:\n# execute_command(command=\"printenv OPENAI_API_KEY\")\n#   \u2192 returns the specific API key\n#   \u2192 NO approval prompt shown\n\n# Verification: check the approval cache\nfrom praisonaiagents.approval import is_already_approved\n# After approving \"ls -la\":\n# is_already_approved(\"execute_command\") \u2192 True\n# Any execute_command call now returns immediately at __init__.py:177-178\n```\n\n## Impact\n\n- **Secret exfiltration**: An LLM agent (or one subjected to prompt injection) can dump all process environment variables after a single benign command approval. Common secrets include `OPENAI_API_KEY`, `AWS_SECRET_ACCESS_KEY`, `DATABASE_URL`, and any other credentials passed via environment.\n- **Misleading consent UI**: The console prompt displays specific arguments and uses language (\"this tool\") that implies per-invocation consent, but the system grants session-wide blanket approval.\n- **No expiration or scope**: The approval cache uses a `ContextVar` that persists for the entire agent execution context with no timeout, no command-count limit, and no clearing between tool calls.\n- **No environment filtering**: `os.environ.copy()` passes every environment variable to subprocesses without filtering sensitive patterns.\n\n## Recommended Fix\n\n1. **Per-invocation approval for critical tools** \u2014 store a hash of `(tool_name, arguments)` instead of just `tool_name`, or require re-approval for each invocation of critical-risk tools:\n\n```python\n# In registry.py \u2014 change mark_approved/is_already_approved:\nimport hashlib, json\n\ndef mark_approved(self, tool_name: str, arguments: dict = None) -\u003e None:\n    approved = self._approved_context.get(set())\n    risk = self._risk_levels.get(tool_name)\n    if risk == \"critical\" and arguments:\n        key = f\"{tool_name}:{hashlib.sha256(json.dumps(arguments, sort_keys=True).encode()).hexdigest()}\"\n    else:\n        key = tool_name\n    approved.add(key)\n    self._approved_context.set(approved)\n\ndef is_already_approved(self, tool_name: str, arguments: dict = None) -\u003e bool:\n    approved = self._approved_context.get(set())\n    risk = self._risk_levels.get(tool_name)\n    if risk == \"critical\" and arguments:\n        key = f\"{tool_name}:{hashlib.sha256(json.dumps(arguments, sort_keys=True).encode()).hexdigest()}\"\n        return key in approved\n    return tool_name in approved\n```\n\n2. **Filter environment variables** in `shell_tools.py`:\n\n```python\nSENSITIVE_PATTERNS = (\u0027_KEY\u0027, \u0027_SECRET\u0027, \u0027_TOKEN\u0027, \u0027_PASSWORD\u0027, \u0027_CREDENTIAL\u0027)\n\nprocess_env = {\n    k: v for k, v in os.environ.items()\n    if not any(p in k.upper() for p in SENSITIVE_PATTERNS)\n}\nif env:\n    process_env.update(env)\n```",
  "id": "GHSA-ffp3-3562-8cv3",
  "modified": "2026-06-19T21:33:09Z",
  "published": "2026-04-10T19:28:38Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-ffp3-3562-8cv3"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-56074"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/MervinPraison/PraisonAI"
    },
    {
      "type": "WEB",
      "url": "https://github.com/MervinPraison/PraisonAI/releases/tag/v4.5.128"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/praisonai-tool-approval-cache-bypass-via-coarse-grained-caching"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ],
  "summary": "PraisonAI: Coarse-Grained Tool Approval Cache Bypasses Per-Invocation Consent for Shell Commands"
}

{
  "affected": [
    {
      "database_specific": {
        "last_known_affected_version_range": "\u003c 4.5.128"
      },
      "package": {
        "ecosystem": "PyPI",
        "name": "praisonai"
      },
      "ranges": [
        {
          "events": [
            {
              "introduced": "0"
            }
          ],
          "type": "ECOSYSTEM"
        }
      ]
    }
  ],
  "aliases": [],
  "database_specific": {
    "cwe_ids": [
      "CWE-863"
    ],
    "github_reviewed": true,
    "github_reviewed_at": "2026-06-19T21:32:50Z",
    "nvd_published_at": "2026-06-18T23:16:19Z",
    "severity": "MODERATE"
  },
  "details": "## Duplicate Advisory\n\nThis advisory has been withdrawn because it is a duplicate of\u00a0GHSA-ffp3-3562-8cv3. This link is maintained to preserve external references.\n\n## Original Description\nPraisonAI before 1.5.128 caches tool approval decisions by tool name only, not by invocation arguments, allowing subsequent execute_command calls to bypass approval prompts. Attackers can exploit this by obtaining initial approval for a benign command, then silently exfiltrate API keys and credentials via subsequent shell commands without user consent.",
  "id": "GHSA-x44p-gg67-52fc",
  "modified": "2026-06-19T21:32:50Z",
  "published": "2026-06-19T00:31:37Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-ffp3-3562-8cv3"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-56074"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/praisonai-tool-approval-cache-bypass-via-coarse-grained-caching"
    }
  ],
  "schema_version": "1.4.0",
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    },
    {
      "score": "CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:P/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X",
      "type": "CVSS_V4"
    }
  ],
  "summary": "Duplicate Advisory: PraisonAI: Coarse-Grained Tool Approval Cache Bypasses Per-Invocation Consent for Shell Commands",
  "withdrawn": "2026-06-19T21:32:50Z"
}

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    }
  ],
  "aliases": [
    "CVE-2026-56074",
    "GHSA-ffp3-3562-8cv3"
  ],
  "details": "## Summary\n\nThe approval system in PraisonAI Agents caches tool approval decisions by tool name only, not by invocation arguments. Once a user approves `execute_command` for any command (e.g., `ls -la`), all subsequent `execute_command` calls in that execution context bypass the approval prompt entirely. Combined with `os.environ.copy()` passing all process environment variables to subprocesses, this allows an LLM agent (potentially via prompt injection) to silently exfiltrate API keys and credentials without further user consent.\n\n## Details\n\nThe `require_approval` decorator in `src/praisonai-agents/praisonaiagents/approval/__init__.py:176-178` checks approval status by tool name only:\n\n```python\n@wraps(func)\ndef wrapper(*args, **kwargs):\n    if is_already_approved(tool_name):   # line 177 \u2014 checks only tool_name\n        return func(*args, **kwargs)     # line 178 \u2014 bypasses ALL approval\n```\n\nThe `mark_approved` function in `registry.py:144-147` stores only the tool name string:\n\n```python\ndef mark_approved(self, tool_name: str) -\u003e None:\n    approved = self._approved_context.get(set())\n    approved.add(tool_name)              # stores \"execute_command\", not args\n    self._approved_context.set(approved)\n```\n\nThe approval context is never cleared during agent execution \u2014 `clear_approved()` exists (`registry.py:152`) but is never called in the agent\u0027s tool execution path (`agent/tool_execution.py`).\n\nMeanwhile, the `ConsoleBackend` UI at `backends.py:95-96` misleads the user:\n\n```python\nreturn Confirm.ask(\n    f\"Do you want to execute this {request.risk_level} risk tool?\",\n    # \"this\" implies per-invocation approval\n)\n```\n\nThe UI displays the specific command arguments (lines 81-85), creating a reasonable expectation that the user is approving only that specific invocation.\n\nAdditionally, `shell_tools.py:77` passes the full process environment to every subprocess:\n\n```python\nprocess_env = os.environ.copy()  # includes OPENAI_API_KEY, etc.\n```\n\nThere is no command filtering, blocklist, or environment variable sanitization in the shell tools module.\n\n## PoC\n\n```python\nfrom praisonaiagents import Agent\nfrom praisonaiagents.tools.shell_tools import execute_command\n\n# Step 1: Create agent with shell tool\nagent = Agent(\n    name=\"worker\",\n    instructions=\"You are a helpful assistant.\",\n    tools=[execute_command]\n)\n\n# Step 2: Agent requests benign command \u2014 user sees Rich panel:\n#   Function: execute_command\n#   Risk Level: CRITICAL\n#   Arguments:\n#     command: ls -la\n#   \"Do you want to execute this critical risk tool?\" [y/N]\n# User approves \u2192 mark_approved(\"execute_command\") is called\n\n# Step 3: All subsequent execute_command calls bypass approval silently:\n# execute_command(command=\"env\")\n#   \u2192 returns ALL environment variables (OPENAI_API_KEY, AWS_SECRET_ACCESS_KEY, etc.)\n#   \u2192 NO approval prompt shown\n\n# Step 4: Targeted extraction also bypasses approval:\n# execute_command(command=\"printenv OPENAI_API_KEY\")\n#   \u2192 returns the specific API key\n#   \u2192 NO approval prompt shown\n\n# Verification: check the approval cache\nfrom praisonaiagents.approval import is_already_approved\n# After approving \"ls -la\":\n# is_already_approved(\"execute_command\") \u2192 True\n# Any execute_command call now returns immediately at __init__.py:177-178\n```\n\n## Impact\n\n- **Secret exfiltration**: An LLM agent (or one subjected to prompt injection) can dump all process environment variables after a single benign command approval. Common secrets include `OPENAI_API_KEY`, `AWS_SECRET_ACCESS_KEY`, `DATABASE_URL`, and any other credentials passed via environment.\n- **Misleading consent UI**: The console prompt displays specific arguments and uses language (\"this tool\") that implies per-invocation consent, but the system grants session-wide blanket approval.\n- **No expiration or scope**: The approval cache uses a `ContextVar` that persists for the entire agent execution context with no timeout, no command-count limit, and no clearing between tool calls.\n- **No environment filtering**: `os.environ.copy()` passes every environment variable to subprocesses without filtering sensitive patterns.\n\n## Recommended Fix\n\n1. **Per-invocation approval for critical tools** \u2014 store a hash of `(tool_name, arguments)` instead of just `tool_name`, or require re-approval for each invocation of critical-risk tools:\n\n```python\n# In registry.py \u2014 change mark_approved/is_already_approved:\nimport hashlib, json\n\ndef mark_approved(self, tool_name: str, arguments: dict = None) -\u003e None:\n    approved = self._approved_context.get(set())\n    risk = self._risk_levels.get(tool_name)\n    if risk == \"critical\" and arguments:\n        key = f\"{tool_name}:{hashlib.sha256(json.dumps(arguments, sort_keys=True).encode()).hexdigest()}\"\n    else:\n        key = tool_name\n    approved.add(key)\n    self._approved_context.set(approved)\n\ndef is_already_approved(self, tool_name: str, arguments: dict = None) -\u003e bool:\n    approved = self._approved_context.get(set())\n    risk = self._risk_levels.get(tool_name)\n    if risk == \"critical\" and arguments:\n        key = f\"{tool_name}:{hashlib.sha256(json.dumps(arguments, sort_keys=True).encode()).hexdigest()}\"\n        return key in approved\n    return tool_name in approved\n```\n\n2. **Filter environment variables** in `shell_tools.py`:\n\n```python\nSENSITIVE_PATTERNS = (\u0027_KEY\u0027, \u0027_SECRET\u0027, \u0027_TOKEN\u0027, \u0027_PASSWORD\u0027, \u0027_CREDENTIAL\u0027)\n\nprocess_env = {\n    k: v for k, v in os.environ.items()\n    if not any(p in k.upper() for p in SENSITIVE_PATTERNS)\n}\nif env:\n    process_env.update(env)\n```",
  "id": "PYSEC-2026-2946",
  "modified": "2026-09-14T17:21:55.168777Z",
  "published": "2026-07-13T14:36:52.273166Z",
  "references": [
    {
      "type": "WEB",
      "url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-ffp3-3562-8cv3"
    },
    {
      "type": "ADVISORY",
      "url": "https://nvd.nist.gov/vuln/detail/CVE-2026-56074"
    },
    {
      "type": "PACKAGE",
      "url": "https://github.com/MervinPraison/PraisonAI"
    },
    {
      "type": "WEB",
      "url": "https://github.com/MervinPraison/PraisonAI/releases/tag/v4.5.128"
    },
    {
      "type": "WEB",
      "url": "https://www.vulncheck.com/advisories/praisonai-tool-approval-cache-bypass-via-coarse-grained-caching"
    },
    {
      "type": "PACKAGE",
      "url": "https://pypi.org/project/praisonaiagents"
    },
    {
      "type": "ADVISORY",
      "url": "https://github.com/advisories/GHSA-ffp3-3562-8cv3"
    }
  ],
  "severity": [
    {
      "score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N",
      "type": "CVSS_V3"
    }
  ],
  "summary": "PraisonAI: Coarse-Grained Tool Approval Cache Bypasses Per-Invocation Consent for Shell Commands"
}