Praison
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Path traversal via symlink exploitation in PraisonAI multi-agent teams system allows remote unauthenticated attackers to write arbitrary files outside intended directories during recipe operations (pull/publish/unpack). The _safe_extractall helper validates archive member names but fails to validate symlink targets (linkname attribute), enabling attackers to craft malicious tar bundles containing symlinks pointing outside extraction directories followed by files traversing through those symlinks. Affects versions prior to 4.6.37. EPSS data unavailable, no CISA KEV listing, and no public POC identified at time of analysis, suggesting limited observed exploitation despite network-accessible attack vector.
Remote attackers can invoke arbitrary application callables in PraisonAI multi-agent systems by manipulating tool-call names to bypass tool declaration controls. Vulnerable versions (praisonai <4.6.37, praisonaiagents <1.6.37) resolve unmatched tool names against module globals and __main__ namespaces without permission validation when _perm_allow is None (default configuration). This enables unauthorized function execution beyond the intended tool list, allowing integrity compromise and potential information disclosure. Patched versions 4.6.37 and 1.6.37 address the tool name resolution vulnerability.
Remote unauthenticated access to PraisonAI's legacy Flask API server allows attackers to execute configured agent workflows without authentication. Versions 2.5.6 through 4.6.33 ship with authentication disabled by default on the Flask server, enabling any network-accessible caller to trigger agents.yaml workflows via the /chat endpoint and access agent configurations through /agents. Patch released in version 4.6.34. CVSS 7.3 with network vector and no privileges required (AV:N/AC:L/PR:N/UI:N) indicates this is remotely exploitable against default configurations, though impact is limited to low confidentiality, integrity, and availability (C:L/I:L/A:L).
Arbitrary file write in PraisonAI's MCP server escalates to remote code execution through path traversal when user interaction triggers malicious tool calls. The praisonai mcp serve daemon accepts attacker-controlled path arguments without validation, allowing writes outside the intended ~/.praison/rules/ directory. Attackers can drop Python .pth files into site-packages to achieve code execution in any subsequent Python process run by the victim user. CVSS 9.4 with network vector and low complexity, though exploitation requires user interaction (PR:N/UI:P). No active exploitation confirmed (not in CISA KEV) and no public POC identified at time of analysis, but the detailed advisory provides sufficient information for weaponization.
Command injection in PraisonAI's MCP server command handler enables remote unauthenticated attackers to execute arbitrary operating system commands. The vulnerability exists in parse_mcp_command() which accepts MCP server commands without validating executables or arguments, allowing injection of shell commands like 'bash -c', 'python -c', or '/bin/sh -c' with inline code execution. GitHub security advisory GHSA-9qhq-v63v-fv3j confirms this is an incomplete fix for CVE-2026-34935. Vendor-released patch version 4.6.9 (upstream version 1.5.69) implements an allowlist of permitted MCP executables and validates commands against ALLOWED_MCP_COMMANDS. No active exploitation confirmed (not in CISA KEV); proof-of-concept exploit code published in advisory demonstrates trivial exploitation.
SQL injection in PraisonAI's multi-backend conversation storage system allows authenticated attackers to execute arbitrary SQL commands. The incomplete fix for CVE-2026-40315 validated input only in SQLiteConversationStore, leaving nine other database backends (MySQL, PostgreSQL, Turso, SingleStore, Supabase, SurrealDB, and their async variants) vulnerable to f-string SQL injection via unvalidated table_prefix and schema parameters. 52 injection points exist across the codebase. Exploitable in multi-tenant deployments or API-driven configurations where table_prefix is derived from external input. Patches released in praisonai 4.6.9 and praisonaiagents 1.6.9 address all affected backends. EPSS and KEV data unavailable; no public POC confirmed at time of analysis.
Remote code execution in PraisonAI multi-agent framework (versions prior to 4.5.128) allows unauthenticated attackers to execute arbitrary code via malicious template files fetched from remote sources. The framework downloads and executes template files without integrity verification, origin validation, or user confirmation, creating a supply chain attack vector. Attackers with network access can distribute weaponized templates that execute when retrieved by victims, achieving high confidentiality and integrity compromise with scope change. No public exploit identified at time of analysis.
SQL and CQL injection vulnerability in PraisonAI multi-agent teams system versions 2.4.1 through 4.6.33 allows authenticated attackers to execute arbitrary SQL or CQL commands by injecting malicious collection names into knowledge-store implementations. The vulnerability affects applications that pass untrusted collection names to optional SQL/CQL-backed storage backends, enabling data exfiltration, modification, or deletion with low complexity exploitation.
Path traversal via symlink exploitation in PraisonAI multi-agent teams system allows remote unauthenticated attackers to write arbitrary files outside intended directories during recipe operations (pull/publish/unpack). The _safe_extractall helper validates archive member names but fails to validate symlink targets (linkname attribute), enabling attackers to craft malicious tar bundles containing symlinks pointing outside extraction directories followed by files traversing through those symlinks. Affects versions prior to 4.6.37. EPSS data unavailable, no CISA KEV listing, and no public POC identified at time of analysis, suggesting limited observed exploitation despite network-accessible attack vector.
Remote attackers can invoke arbitrary application callables in PraisonAI multi-agent systems by manipulating tool-call names to bypass tool declaration controls. Vulnerable versions (praisonai <4.6.37, praisonaiagents <1.6.37) resolve unmatched tool names against module globals and __main__ namespaces without permission validation when _perm_allow is None (default configuration). This enables unauthorized function execution beyond the intended tool list, allowing integrity compromise and potential information disclosure. Patched versions 4.6.37 and 1.6.37 address the tool name resolution vulnerability.
Remote unauthenticated access to PraisonAI's legacy Flask API server allows attackers to execute configured agent workflows without authentication. Versions 2.5.6 through 4.6.33 ship with authentication disabled by default on the Flask server, enabling any network-accessible caller to trigger agents.yaml workflows via the /chat endpoint and access agent configurations through /agents. Patch released in version 4.6.34. CVSS 7.3 with network vector and no privileges required (AV:N/AC:L/PR:N/UI:N) indicates this is remotely exploitable against default configurations, though impact is limited to low confidentiality, integrity, and availability (C:L/I:L/A:L).
Arbitrary file write in PraisonAI's MCP server escalates to remote code execution through path traversal when user interaction triggers malicious tool calls. The praisonai mcp serve daemon accepts attacker-controlled path arguments without validation, allowing writes outside the intended ~/.praison/rules/ directory. Attackers can drop Python .pth files into site-packages to achieve code execution in any subsequent Python process run by the victim user. CVSS 9.4 with network vector and low complexity, though exploitation requires user interaction (PR:N/UI:P). No active exploitation confirmed (not in CISA KEV) and no public POC identified at time of analysis, but the detailed advisory provides sufficient information for weaponization.
Command injection in PraisonAI's MCP server command handler enables remote unauthenticated attackers to execute arbitrary operating system commands. The vulnerability exists in parse_mcp_command() which accepts MCP server commands without validating executables or arguments, allowing injection of shell commands like 'bash -c', 'python -c', or '/bin/sh -c' with inline code execution. GitHub security advisory GHSA-9qhq-v63v-fv3j confirms this is an incomplete fix for CVE-2026-34935. Vendor-released patch version 4.6.9 (upstream version 1.5.69) implements an allowlist of permitted MCP executables and validates commands against ALLOWED_MCP_COMMANDS. No active exploitation confirmed (not in CISA KEV); proof-of-concept exploit code published in advisory demonstrates trivial exploitation.
SQL injection in PraisonAI's multi-backend conversation storage system allows authenticated attackers to execute arbitrary SQL commands. The incomplete fix for CVE-2026-40315 validated input only in SQLiteConversationStore, leaving nine other database backends (MySQL, PostgreSQL, Turso, SingleStore, Supabase, SurrealDB, and their async variants) vulnerable to f-string SQL injection via unvalidated table_prefix and schema parameters. 52 injection points exist across the codebase. Exploitable in multi-tenant deployments or API-driven configurations where table_prefix is derived from external input. Patches released in praisonai 4.6.9 and praisonaiagents 1.6.9 address all affected backends. EPSS and KEV data unavailable; no public POC confirmed at time of analysis.
Remote code execution in PraisonAI multi-agent framework (versions prior to 4.5.128) allows unauthenticated attackers to execute arbitrary code via malicious template files fetched from remote sources. The framework downloads and executes template files without integrity verification, origin validation, or user confirmation, creating a supply chain attack vector. Attackers with network access can distribute weaponized templates that execute when retrieved by victims, achieving high confidentiality and integrity compromise with scope change. No public exploit identified at time of analysis.
SQL and CQL injection vulnerability in PraisonAI multi-agent teams system versions 2.4.1 through 4.6.33 allows authenticated attackers to execute arbitrary SQL or CQL commands by injecting malicious collection names into knowledge-store implementations. The vulnerability affects applications that pass untrusted collection names to optional SQL/CQL-backed storage backends, enabling data exfiltration, modification, or deletion with low complexity exploitation.