extensions/feishu/src/docx.ts:1
[AGENTS: Blacklist, Chaos, Cipher, Compliance, Entropy, Exploit, Fuse, Gatekeeper, Gateway, Harbor, Infiltrator, Lockdown, Mirage, Passkey, Pedant, Phantom, Provenance, Razor, Sanitizer, Sentinel, Trace, Vault, Vector, Warden, Weights]ai_provenance, attack_chains, attack_surface, auth, business_logic, configuration, containers, correctness, credentials, cryptography, data_exposure, edge_cases, edge_security, error_security, false_confidence, input_validation, logging, model_supply_chain, output_encoding, privacy, randomness, regulatory, sanitization, secrets, security
**Perspective 1:** The `resolveUploadInput` function accepts multiple input sources (url, filePath, imageInput) but doesn't properly validate the inputs before processing. The function handles data URIs, local paths, and base64 strings but lacks comprehensive validation for each type. For example, base64 validation regex doesn't account for all valid base64 characters and could allow malicious content.
**Perspective 2:** The function validates base64 length then creates Buffer anyway. If many concurrent requests with large base64 payloads arrive, memory could spike despite length check.
**Perspective 3:** The resolveUploadInput function accepts file paths, URLs, and base64/image data without proper validation. File paths can contain directory traversal sequences (../../../), and URLs are not validated for SSRF risks. The function uses existsSync() for local paths but doesn't sanitize path components before checking existence.
**Perspective 4:** The code extensively uses Feishu API responses without proper validation of the response structure. Functions like `convertMarkdown`, `insertBlocks`, and `uploadImageToDocx` directly access properties like `res.data`, `res.code`, `res.msg` without validating the response shape. This could lead to runtime errors if the API returns unexpected data structures.
**Perspective 5:** The `extractImageUrls` function uses a simple regex to extract URLs from markdown but doesn't validate the extracted URLs. It only checks for http:// or https:// prefixes, but doesn't validate URL structure or prevent SSRF attacks. The extracted URLs are later used in `downloadImage` which could be exploited.
**Perspective 6:** Functions like `createTable`, `writeTableCells`, and `createTableWithValues` accept user-provided values without sanitization. The values are directly passed to Feishu API calls which could lead to injection attacks or unexpected behavior.
**Perspective 7:** The resolveUploadInput function validates estimated bytes but doesn't handle cases where the actual decoded buffer size differs from estimation due to malformed base64.
**Perspective 8:** The resolveUploadInput function handles file paths including user-controlled input (filePath, imageInput). While some validation exists, the use of homedir() replacement and isAbsolute() checks may not fully prevent path traversal attacks. An attacker could potentially access sensitive files on the server.
**Perspective 9:** The convertMarkdownWithFallback and chunkedInsertBlocks functions handle large documents by splitting and retrying. An attacker could craft malicious markdown that causes infinite recursion or memory exhaustion. The image processing functions (processImages, uploadImageToDocx) download remote images without proper sandboxing, enabling SSRF attacks. The resolveUploadInput function accepts multiple input sources that could be chained to bypass size limits.
**Perspective 10:** The Feishu document handling code processes sensitive operations like document creation, image uploads, and file operations but doesn't use cryptographically secure random number generation for any generated IDs or tokens. The code relies on Feishu API-generated tokens but doesn't generate any local secure identifiers.
**Perspective 11:** The convertMarkdown function processes user-provided markdown content without sanitizing HTML elements. When this markdown is converted to blocks and rendered in Feishu documents, any HTML tags in the markdown could be interpreted by the Feishu rendering engine, potentially leading to XSS if the content is displayed in web interfaces.
**Perspective 12:** The Feishu document operations (create, read, write, delete) don't validate if the authenticated user has appropriate permissions for the document or folder. This could lead to unauthorized access to sensitive documents.
**Perspective 13:** The file contains test code with hardcoded credentials like 'cli_test' and 'sec_test' which could be accidentally used in production. While this is test code, hardcoded credentials should be avoided even in test environments as they can be accidentally committed or deployed.
**Perspective 14:** The extractImageUrls function accepts both http:// and https:// URLs without validation. HTTP URLs could expose image data to interception during download via fetchRemoteMedia.
**Perspective 15:** The base64 validation regex /^[A-Za-z0-9+/]+=*$/ does not enforce proper padding length (must be 0, 1, or 2 '=' characters). Malformed padding could cause decoding errors or buffer overflows.
**Perspective 16:** The function `downloadImage` calls `getFeishuRuntime().channel.media.fetchRemoteMedia({ url, maxBytes })` without validating or restricting the URL scheme. This could allow Server-Side Request Forgery (SSRF) attacks if user-controlled URLs are passed to the function. While there may be upstream validation, the code doesn't show explicit URL validation or allowlisting.
**Perspective 17:** The `resolveUploadInput` function accepts `filePath` and `imageInput` parameters that can be local file paths. While there's some validation with `isAbsolute()` and `existsSync()`, the code doesn't explicitly prevent directory traversal attacks (e.g., `../../../etc/passwd`). If user-controlled paths are passed, this could lead to unauthorized file reads.
**Perspective 18:** The code contains multiple error handling blocks that return error messages containing potentially sensitive information from Feishu API responses (e.g., `res.msg`). These error messages could contain API keys, tokens, or other sensitive data that might be exposed to end users or logged.
**Perspective 19:** The convertMarkdown function accepts arbitrary markdown content without size validation. While there's chunking logic (splitMarkdownBySize), there's no gateway-level request size limit to prevent DoS via extremely large markdown payloads.
**Perspective 20:** The extractImageUrls function extracts URLs from markdown but doesn't validate them against allow/deny lists. This could allow SSRF attacks if the bot processes malicious markdown containing internal URLs.
**Perspective 21:** The uploadImageToDocx function passes Buffer directly to SDK but doesn't handle cases where the SDK might reject large buffers or where the upload could fail due to network issues. No retry logic or proper error propagation.
**Perspective 22:** The insertBlocks function inserts blocks one at a time with sequential API calls, but if one insert fails, the function throws an error leaving the document in an inconsistent state (some blocks inserted, some not).
**Perspective 23:** The downloadImage function calls `new URL(url)` without try-catch. Invalid URLs will throw unhandled TypeError, crashing the process.
**Perspective 24:** The base64 validation regex /^[A-Za-z0-9+/]+=*$/ is incomplete. It doesn't validate proper padding (should be 0-2 '=' at end) and doesn't reject invalid characters like spaces. Additionally, base64 URL-safe variants using '-' and '_' are rejected, which could cause issues with some data URIs.
**Perspective 25:** The data URI parsing splits on the first comma, but doesn't validate the MIME type format. An attacker could craft a data URI like 'data:text/html;base64,PHNjcmlwdD5hbGVydCgxKTwvc2NyaXB0Pg==' which would be accepted as valid. While this is processed as image data, improper handling could lead to XSS if the content is later interpreted as HTML.
**Perspective 26:** The code makes numerous Feishu API calls but doesn't consistently handle error responses. Many API calls check `res.code !== 0` but some error messages may leak internal details. The error handling pattern varies across functions, potentially exposing stack traces or sensitive information in production.
**Perspective 27:** Line 1015 uses `console.error` to log image processing failures. In production, this could leak sensitive information to logs accessible to unauthorized users. Console logging may not be properly configured in production environments.
**Perspective 28:** The `convertMarkdown` function accepts arbitrary markdown strings without size validation. While there's a fallback mechanism for large content, there's no upfront validation of input size which could lead to memory exhaustion or API rate limiting issues.
**Perspective 29:** The Feishu document processing module handles user documents, markdown content, and images without implementing data classification or PII detection. Documents may contain sensitive personal information, but there's no mechanism to identify, classify, or apply special handling to sensitive content. The module processes all content uniformly, potentially exposing PII through document operations.
**Perspective 30:** The Feishu document module performs create, read, update, and delete operations on user documents without comprehensive audit logging. There's no tracking of who accessed/modified which documents, when, or why. This violates GDPR's accountability principle and makes it impossible to demonstrate compliance or investigate data breaches.
**Perspective 31:** The resolveUploadInput function accepts multiple input sources (URL, file path, image input) but lacks comprehensive validation for malicious file paths or URLs. While some validation exists for data URIs and base64, the file path handling could be vulnerable to path traversal attacks.
**Perspective 32:** The code uses hardcoded maximum byte limits for image uploads (e.g., maxBytes parameter) but these limits are not configurable through the plugin configuration schema. This could lead to denial of service if attackers upload large files.
**Perspective 33:** The docToken parameter is used throughout the file without validation. Empty strings, null values, or malformed tokens could cause API failures or unexpected behavior.
**Perspective 34:** The code makes numerous API calls to Feishu services without timeout configurations. Network issues could cause indefinite hanging.
**Perspective 35:** senderNameCache is a global Map shared across all requests. Concurrent reads/writes could cause race conditions.
**Perspective 36:** The extractImageUrls function extracts URLs from markdown content without validating or sanitizing them. These URLs are later used in downloadImage function which fetches remote media. This could lead to SSRF attacks where an attacker could make the server request internal resources.
**Perspective 37:** The base64 validation regex /^[A-Za-z0-9+/]+=*$/ may not be strict enough and could allow padding attacks or other encoding issues. Node's Buffer.from is permissive with base64, which could lead to unexpected behavior.
**Perspective 38:** The uploadImageToDocx and uploadFileBlock functions accept arbitrary file buffers without proper validation of file types, sizes, or malicious content. While there are size limits, there's no validation for file types, MIME type consistency, or protection against malicious files.
**Perspective 39:** The resolveUploadInput function validates base64 strings with regex /^[A-Za-z0-9+/]+=*$/ which doesn't properly validate padding. Attackers could craft malformed base64 that passes regex but causes decoding issues or buffer overflows.
**Perspective 40:** The createDoc function creates Feishu documents without any rate limiting or quota enforcement. An attacker could spam document creation requests, potentially exhausting API quotas or creating excessive resources in the Feishu workspace.
**Perspective 41:** The convertMarkdownWithFallback function recursively splits markdown content but doesn't enforce maximum total size limits. An attacker could submit extremely large markdown content that would be processed in many small chunks, consuming excessive API resources.
**Perspective 42:** While there's a maxBytes parameter for image uploads, the actual enforcement happens late in the processing pipeline after some resources have already been allocated. An attacker could attempt to upload many large images simultaneously before size checks occur.
**Perspective 43:** The code includes validation for base64 data URIs with regex patterns and byte estimation, but then uses Buffer.from() which will still decode invalid base64 (though with warnings). The validation claims to reject 'garbage bytes' but Node's Buffer.from() is permissive and will decode malformed strings into arbitrary bytes. The validation is incomplete security theater.
**Perspective 44:** The resolveUploadInput function has logic to detect absolute paths and check if they exist, but if an absolute path doesn't exist, it throws an error rather than falling through to base64 decoding. However, the comment claims this prevents 'silently uploading garbage bytes', but the actual flow still allows base64 input that starts with '/' (like JPEG base64 '/9j/') to be misinterpreted as absolute paths. This creates a false sense of security about input validation.
**Perspective 45:** The Feishu document operations (create, read, write, update, delete) lack comprehensive audit logging. SOC 2 CC6.1 requires logging of security events including data access and modifications. HIPAA Security Rule §164.312(b) requires audit controls to record and examine activity in information systems that contain or use electronic protected health information (ePHI). The code performs document operations without logging who accessed/modified what content and when.
**Perspective 46:** The document operations rely on Feishu API permissions but lack application-level access control validation. SOC 2 CC6.1 requires logical access controls to protect against unauthorized access. HIPAA §164.312(a)(1) requires implementation of technical policies and procedures that allow only authorized persons to access ePHI. The code doesn't validate if the requesting user/account has appropriate authorization for specific document operations beyond the Feishu API token.
**Perspective 47:** The code imports '@larksuiteoapi/node-sdk' without specifying a pinned version or checksum verification. This external SDK could be compromised via supply chain attack, potentially affecting document processing functionality.
**Perspective 48:** The code imports type definitions from '@sinclair/typebox' and 'openclaw/plugin-sdk/feishu' without integrity verification. Compromised type definitions could lead to type confusion or injection attacks.
**Perspective 49:** The code downloads and processes images from external URLs without verifying file integrity or checking for malicious content before processing.
**Perspective 50:** The resolveUploadInput function processes base64-encoded image data without comprehensive validation, potentially allowing malicious payloads.
**Perspective 51:** The docx.ts module provides extensive document manipulation capabilities including file uploads, image processing, and document creation/writing. This creates a large attack surface for file upload vulnerabilities, path traversal, and potential SSRF via image URL fetching. The module accepts multiple input sources (URLs, file paths, base64 data) without sufficient validation of external URLs or path traversal prevention.
**Perspective 52:** The code imports '@larksuiteoapi/node-sdk' which appears to be a hallucinated or non-existent package. This is likely AI-generated code referencing a package that doesn't exist in the public registry or the project's dependencies.
**Perspective 53:** The base64 validation uses regex.test() which may have timing variations based on input length and pattern. While not critical for image uploads, it could leak information about invalid characters.
**Perspective 54:** The uploadImageToDocx function accepts Buffer data without validating Content-Type headers. While the SDK may validate internally, there's no gateway-level validation to prevent malicious file uploads.
**Perspective 55:** The function recursively calls itself with depth parameter, but if markdown length is always >= 2 and splitMarkdownBySize returns chunks with length <= 1, it could infinite loop. The condition `if (chunks.length <= 1) { throw error; }` prevents this, but edge cases exist.
**Perspective 56:** The code extracts filenames from URLs using new URL(url).pathname.split('/').pop(). This doesn't sanitize the extracted filename, which could contain special characters or path traversal sequences. If the filename is used in file system operations, it could lead to path injection.
**Perspective 57:** The module processes documents but doesn't implement data retention policies. Temporary files, cached content, or processed data may persist indefinitely without cleanup mechanisms. This violates GDPR's storage limitation principle which requires data to be kept only as long as necessary.
**Perspective 58:** splitMarkdownByHeadings and splitMarkdownBySize functions split by newline characters but don't handle Unicode line separators (\u2028, \u2029) or combined emoji.
**Perspective 59:** Document operations (create, read, write, update, delete) don't have comprehensive audit logging. While errors are logged, successful operations that modify documents aren't tracked in an audit trail, making it difficult to track who changed what and when.
**Perspective 60:** The resolveUploadInput function handles local file paths with ~ expansion but doesn't properly sanitize paths, potentially allowing path traversal attacks if the input is controlled by an attacker.
**Perspective 61:** The document operations don't consider data classification levels. SOC 2 CC6.8 requires classification of information to enable appropriate protection. HIPAA requires special handling for PHI. The code treats all documents equally regardless of sensitivity, potentially allowing sensitive data to be processed without additional safeguards.
**Perspective 62:** Multiple functions parse JSON content from external APIs without strict schema validation, potentially allowing malformed or malicious data structures.
**Perspective 63:** File upload functionality doesn't track provenance metadata (source, uploader, timestamp) for uploaded documents and images.
Suggested Fix
Implement strict validation for each input type: validate data URI format, enforce strict base64 validation, validate file paths against directory traversal, and implement size limits before processing.