{"id":"PYSEC-2026-3532","summary":"PraisonAI: IMAP Command Injection via Unsanitized Email Search Parameters","details":"## Summary\n\nThe email search tool in `src/praisonai-agents/praisonaiagents/tools/email_tools.py` constructs IMAP SEARCH commands by interpolating LLM-controlled parameters (from_addr, subject, query) directly into IMAP protocol strings using f-string formatting with double-quote delimiters. An attacker who can influence the arguments to the `search_emails` or `reply_email` tool (via crafted agent prompts) can inject arbitrary IMAP commands, potentially exfiltrating email data from other folders, deleting emails, or performing other unauthorized IMAP operations.\n## Details\n\n**Vulnerable code (lines 493–502):**\n```python\ncriteria = []\nif from_addr:\n    criteria.append(f'FROM \"{from_addr}\"')\nif subject:\n    criteria.append(f'SUBJECT \"{subject}\"')\nif query:\n    criteria.append(f'TEXT \"{query}\"')\nif not criteria:\n    criteria.append(\"ALL\")\nsearch_str = \" \".join(criteria)\nstatus, data = mail.search(None, search_str)\n```\n\nThe `from_addr`, `subject`, and `query` parameters originate from LLM tool call arguments (the `search_emails` public function at line 665). These values flow through without any sanitization or escaping. The double-quote (`\"`) characters in these parameters allow breaking out of the IMAP SEARCH quoted string context.\n\n**Additional injection points:**\n- Line 416: `mail.search(None, f'HEADER Message-ID \"{search_id}\"')`\n- Line 447: Same pattern in `_smtp_reply_email`\n- Line 542: Same pattern in `_smtp_archive_email`\n\nThe `search_id` / `message_id` parameter in these functions is also LLM-controlled via the `reply_email` and `archive_email` public tool functions.\n\n**Reachability:** The `search_emails`, `reply_email`, and `archive_email` functions are exposed as agent tools. They are reachable when an agent is configured with email tools (EMAIL_ADDRESS + EMAIL_PASSWORD environment variables set). This is a documented deployment scenario for email-capable agents.\n\n## PoC\n\n**Setup:** Requires an IMAP server (not run here — this is a static proof). The vulnerability is demonstrated by tracing the data flow.\n\n**Positive trigger — IMAP injection via `search_emails`:**\nAn LLM agent processing a crafted prompt calls:\n```python\nsearch_emails(from_addr='user@example.com\" LOGOUT')\n```\nThis produces the IMAP command:\n```\nSEARCH FROM \"user@example.com\" LOGOUT\"\n```\nThe `LOGOUT` command is injected after the prematurely closed quoted string, causing the IMAP connection to be terminated.\n\n**More severe injection — exfiltrate emails from another folder:**\n```python\nsearch_emails(query='\" SEARCH RETURN (MIN) ALL')\n```\nProduces: `TEXT \"\" SEARCH RETURN (MIN) ALL\"` — injects a secondary SEARCH command.\n\n**Negative control — legitimate search:**\n```python\nsearch_emails(from_addr='user@example.com')\n```\nProduces: `FROM \"user@example.com\"` — correct, no injection.\n\n**Cleanup:** No persistent changes for read-only injection. For destructive injection (DELETE, EXPUNGE), impact persists.\n\n## Impact\n\nAn attacker who can craft prompts that cause an LLM agent to call `search_emails` with injection payloads can:\n\n- **Terminate IMAP connections** (denial of service)\n- **Inject arbitrary IMAP commands** — including LIST (enumerate folders), SELECT (switch folders), FETCH (read emails from other mailboxes), STORE (modify flags), COPY/MOVE (move emails), DELETE/EXPUNGE (permanently delete emails)\n- **Exfiltrate email contents** from folders the user did not intend to expose to the agent\n- **Permanently delete emails** via injected DELETE + EXPUNGE commands\n\nThe attack requires the IMAP backend to be configured (EMAIL_ADDRESS + EMAIL_PASSWORD env vars), which is a documented and common deployment for email-capable agents.\n\n## Suggested remediation\n\n1. **Escape double-quote characters** in IMAP parameters. Per RFC 3501, literal strings use `{n}\\r\\n` format or quoted strings with `\\` escaping:\n```python\ndef _escape_imap_string(s: str) -\u003e str:\n    \"\"\"Escape a string for safe use in IMAP quoted strings.\"\"\"\n    # Use IMAP literal syntax for safety: {length}\\r\\n\u003cdata\u003e\n    encoded = s.encode('utf-8')\n    return f'{{{len(encoded)}}}\\r\\n{encoded}'\n```\n\n2. Use IMAP literal syntax (`{n}\\r\\ndata`) instead of quoted strings for all user-controlled parameters. This prevents any injection regardless of content.\n\n3. Apply the escaping to all IMAP search criteria parameters: `from_addr`, `subject`, `query`, and `search_id`/`message_id`.","aliases":["CVE-2026-57130","GHSA-c969-5x3p-vq3v"],"modified":"2026-07-23T15:00:22.408575275Z","published":"2026-07-23T11:41:42.796783Z","references":[{"type":"WEB","url":"https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-c969-5x3p-vq3v"},{"type":"PACKAGE","url":"https://github.com/MervinPraison/PraisonAI"},{"type":"PACKAGE","url":"https://pypi.org/project/praisonaiagents"},{"type":"ADVISORY","url":"https://github.com/advisories/GHSA-c969-5x3p-vq3v"},{"type":"ADVISORY","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-57130"}],"affected":[{"package":{"name":"praisonaiagents","ecosystem":"PyPI","purl":"pkg:pypi/praisonaiagents"},"ranges":[{"type":"ECOSYSTEM","events":[{"introduced":"0"},{"fixed":"1.6.59"}]}],"versions":["0.0.1","0.0.10","0.0.100","0.0.101","0.0.102","0.0.103","0.0.104","0.0.105","0.0.106","0.0.107","0.0.108","0.0.109","0.0.11","0.0.110","0.0.111","0.0.112","0.0.113","0.0.114","0.0.115","0.0.116","0.0.117","0.0.118","0.0.119","0.0.12","0.0.120","0.0.121","0.0.122","0.0.123","0.0.124","0.0.125","0.0.126","0.0.127","0.0.128","0.0.129","0.0.13","0.0.130","0.0.131","0.0.132","0.0.133","0.0.134","0.0.135","0.0.136","0.0.137","0.0.138","0.0.139","0.0.14","0.0.140","0.0.141","0.0.142","0.0.143","0.0.144","0.0.145","0.0.146","0.0.147","0.0.148","0.0.149","0.0.15","0.0.150","0.0.151","0.0.152","0.0.153","0.0.154","0.0.155","0.0.156","0.0.157","0.0.158","0.0.159","0.0.16","0.0.160","0.0.161","0.0.162","0.0.163","0.0.164","0.0.165","0.0.166","0.0.167","0.0.168","0.0.169","0.0.17","0.0.170","0.0.171","0.0.172","0.0.173","0.0.174","0.0.175","0.0.176","0.0.177","0.0.178","0.0.179","0.0.18","0.0.180","0.0.181","0.0.182","0.0.183","0.0.184","0.0.185","0.0.187","0.0.188","0.0.189","0.0.19","0.0.190","0.0.191","0.0.192","0.0.193","0.0.194","0.0.195","0.0.196","0.0.197","0.0.198","0.0.199","0.0.2","0.0.20","0.0.21","0.0.22","0.0.23","0.0.24","0.0.25","0.0.26","0.0.27","0.0.28","0.0.29","0.0.3","0.0.30","0.0.31","0.0.32","0.0.33","0.0.34","0.0.35","0.0.36","0.0.37","0.0.38","0.0.39","0.0.4","0.0.40","0.0.41","0.0.42","0.0.43","0.0.44","0.0.45","0.0.46","0.0.47","0.0.48","0.0.49","0.0.5","0.0.50","0.0.51","0.0.52","0.0.53","0.0.54","0.0.56","0.0.57","0.0.58","0.0.59","0.0.6","0.0.60","0.0.61","0.0.62","0.0.63","0.0.64","0.0.65","0.0.66","0.0.67","0.0.68","0.0.69","0.0.7","0.0.70","0.0.71","0.0.72","0.0.73","0.0.74","0.0.75","0.0.76","0.0.77","0.0.78","0.0.79","0.0.8","0.0.80","0.0.81","0.0.82","0.0.83","0.0.84","0.0.85","0.0.86","0.0.87","0.0.88","0.0.89","0.0.9","0.0.90","0.0.91","0.0.92","0.0.93","0.0.94","0.0.95","0.0.96","0.0.97","0.0.98","0.0.99","0.1.0","0.1.1","0.1.10","0.1.11","0.1.12","0.1.13","0.1.14","0.1.15","0.1.16","0.1.17","0.1.18","0.1.19","0.1.2","0.1.20","0.1.21","0.1.22","0.1.23","0.1.24","0.1.25","0.1.26","0.1.27","0.1.3","0.1.4","0.1.5","0.1.6","0.1.7","0.1.8","0.1.9","0.10.0","0.10.1","0.10.10","0.10.2","0.10.3","0.10.4","0.10.5","0.10.6","0.10.7","0.10.8","0.10.9","0.11.0","0.11.1","0.11.10","0.11.11","0.11.12","0.11.13","0.11.14","0.11.15","0.11.16","0.11.17","0.11.18","0.11.19","0.11.2","0.11.20","0.11.21","0.11.22","0.11.23","0.11.24","0.11.25","0.11.27","0.11.28","0.11.29","0.11.3","0.11.30","0.11.31","0.11.4","0.11.5","0.11.6","0.11.7","0.11.8","0.11.9","0.12.0","0.12.1","0.12.10","0.12.11","0.12.12","0.12.13","0.12.14","0.12.15","0.12.16","0.12.17","0.12.18","0.12.19","0.12.2","0.12.20","0.12.21","0.12.3","0.12.4","0.12.5","0.12.6","0.12.7","0.12.8","0.12.9","0.13.0","0.13.1","0.13.10","0.13.11","0.13.12","0.13.13","0.13.14","0.13.15","0.13.16","0.13.17","0.13.18","0.13.19","0.13.2","0.13.20","0.13.21","0.13.22","0.13.23","0.13.3","0.13.4","0.13.5","0.13.6","0.13.7","0.13.8","0.13.9","0.14.0","0.14.1","0.14.10","0.14.11","0.14.12","0.14.14","0.14.15","0.14.16","0.14.2","0.14.3","0.14.4","0.14.5","0.14.6","0.14.7","0.14.8","0.14.9","0.15.0","0.15.1","0.15.2","0.15.3","0.2.0","0.2.1","0.2.2","0.3.0","0.3.1","0.3.2","0.3.3","0.3.4","0.4.0","0.4.1","0.5.0","0.5.1","0.5.2","0.5.3","0.6.0","0.6.1","0.6.2","0.6.3","0.6.4","0.6.5","0.6.6","0.6.7","0.6.8","0.7.0","0.7.1","0.8.0","0.8.1","0.9.0","0.9.1","1.0.0","1.1.0","1.2.0","1.2.1","1.2.2","1.2.3","1.2.4","1.3.0","1.3.1","1.4.0","1.4.1","1.4.2","1.4.3","1.4.4","1.4.5","1.4.6","1.4.7","1.4.8","1.5.0","1.5.1","1.5.10","1.5.100","1.5.101","1.5.102","1.5.103","1.5.104","1.5.105","1.5.106","1.5.107","1.5.108","1.5.109","1.5.11","1.5.110","1.5.111","1.5.112","1.5.113","1.5.114","1.5.115","1.5.116","1.5.117","1.5.118","1.5.119","1.5.12","1.5.120","1.5.121","1.5.122","1.5.123","1.5.124","1.5.125","1.5.126","1.5.127","1.5.128","1.5.129","1.5.13","1.5.130","1.5.131","1.5.132","1.5.133","1.5.134","1.5.135","1.5.136","1.5.137","1.5.138","1.5.139","1.5.14","1.5.140","1.5.141","1.5.142","1.5.143","1.5.144","1.5.145","1.5.146","1.5.147","1.5.148","1.5.149","1.5.15","1.5.16","1.5.17","1.5.18","1.5.19","1.5.2","1.5.20","1.5.21","1.5.22","1.5.23","1.5.24","1.5.25","1.5.26","1.5.27","1.5.28","1.5.29","1.5.3","1.5.30"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