Crawl4AI - LLM Credential Exfiltration via base_url and Environment Variable Resolution
Crawl4AI before 0.8.8 contains credential exfiltration vulnerabilities in the Docker API server that allow attackers to redirect LLM API calls to attacker-controlled endpoints and read arbitrary environment variables. Attackers can exploit the unauthenticated /md, /llm, and /llm/job endpoints by supplying a malicious base_url parameter and setting api_token to env:VARIABLE_NAME to exfiltrate provider API keys and server secrets including JWT SECRET_KEY for authentication bypass.
PraisonAI before 1.6.78 Remote Code Execution via CodeAgent
PraisonAI before 1.6.78 contains a remote code execution vulnerability in CodeAgent._execute_python() that executes LLM-generated Python code without AST validation, import restrictions, or sandbox enforcement. Attackers can influence LLM output through prompt injection to exfiltrate all environment secrets and execute arbitrary code on the host system.
PraisonAI before 4.6.78 Arbitrary File Write and Command Execution
PraisonAI before 4.6.78 contains arbitrary file write and command execution vulnerabilities in the AICoder component due to missing path validation and command sanitization in LLM tool calls. Attackers can inject malicious prompts through the chat interface to write files to arbitrary filesystem locations and execute arbitrary shell commands with root privileges.
PraisonAI Platform before 0.1.9 Authorization Bypass via PATCH
PraisonAI Platform (praisonai-platform) before 0.1.9 fails to enforce owner/admin authorization on the PATCH routes for projects, issues, and agents, which only require workspace-member role. A workspace member can modify owner-created records; for projects, a member can reassign lead_id to their own user id and then delete the owner-created project, bypassing the delete route's owner/admin permission check.
PraisonAI before 4.6.78 Prompt Injection Defense Bypass
PraisonAI versions before 4.6.78 contain a prompt injection defense misconfiguration where the block threshold defaults to CRITICAL severity, allowing HIGH-level threats to pass through unblocked. Attackers can submit single-vector prompt injection attacks such as instruction overrides or financial manipulation that trigger HIGH severity detection but are logged without blocking, enabling system prompt extraction and unauthorized tool invocations.
PraisonAI before 1.6.78 SSRF via Crawl4AI Chromium backend
PraisonAI versions before 1.6.78 contain a server-side request forgery vulnerability in the Crawl4AI/Chromium backend that allows attackers to bypass SSRF validation by exploiting DNS rebinding and HTTP redirects. Attackers can craft URLs that resolve to internal services after the initial validation check, enabling the headless browser to follow redirects and read internal responses including sensitive canary values.
PraisonAI AgentMail before 4.6.78 Message Injection via Webhook
PraisonAI AgentMail versions before 4.6.78 lack signature verification in webhook mode, allowing unauthenticated attackers to inject messages with spoofed sender addresses. Attackers can POST crafted message.received events to the webhook endpoint to inject arbitrary content into the agent and trigger replies to attacker-controlled addresses, bypassing sender allow/block lists.
PraisonAI before 4.6.78 SQL/CQL Injection via vector dimension
PraisonAI before 4.6.78 fails to validate the caller-controlled dimension argument in the PGVector and Cassandra knowledge-store create_collection() backends. Although schema, keyspace, and collection-name identifiers are validated, the dimension value (declared as int but not enforced at runtime) is interpolated directly into the vector column of the generated CREATE TABLE DDL. A caller able to influence collection-creation dimensions can pass a string such as '3); DROP TABLE tenant_secrets; --' to inject SQL/CQL tokens into the statement executed by the database driver.
PraisonAI before 4.6.78 Path Traversal via Custom Commands
PraisonAI before 4.6.78 fails to validate file path references in custom command templates, allowing attackers to read files outside the workspace. Attackers can include path traversal sequences like @../outside_secret.txt or absolute paths in project command files to exfiltrate process-readable files into model prompts.
Path traversal in EverOS /api/v1/memory/add via unvalidated sender_id
EverOS is a memory runtime for agents. Prior to 1.0.1, EverOS is vulnerable to path traversal in the POST /api/v1/memory/add ingestion endpoint because the per-message sender_id field was not validated as a path-safe identifier, unlike app_id and project_id. During user-memory extraction, sender_id is used as owner_id and joined into the filesystem path where the extracted episode is persisted as a Markdown file, so a sender_id containing ../ sequences could direct writes outside the configured memory root and allow an unauthenticated caller to create or overwrite .md files at locations writable by the server process with partially attacker-i
Clauster: Non-loopback deployments can serve the dashboard unauthenticated when auth.enabled is unset
### Summary
A Clauster instance bound to a **non-loopback** address (e.g. `0.0.0.0` or a LAN IP) can serve the entire dashboard and its API **without any authentication** — even when the operator has configured a password — if `auth.enabled` is left at its default (`false`). The operator believes the instance is password-protected; in reality every request is served unauthenticated.
### Impact
An unauthenticated attacker with network access to the instance gains full control of the dashboard: list projects, **spawn/stop `claude remote-control` bridges in any project directory**, edit `CLAUDE.md`, read bridge logs, and (where configured) clon
CredSweeper: Recursive archive size-limit bypass in deep scanner allows crafted compressed inputs to exhaust resources
### Summary
CredSweeper's deep scanner does not enforce `recursive_limit_size` as a hard limit. Several recursive scanners fully decompress or fully read attacker-controlled content before the remaining budget is validated, and `AbstractScanner.recursive_scan()` continues processing even when the residual budget is already negative.
This allows a crafted archive to bypass the intended recursive zip-bomb protection and force excessive memory / CPU consumption when deep scanning is enabled (`--depth > 0`). I confirmed this on upstream commit `8b081acf04311eafe8fbd66ea41d02b0a7a4c6f6` / package version `1.15.8`.
The issue has two closely relat
MCP Server Kubernetes < 3.9.0 Argument Injection via kubectl Structured Tools
MCP Server Kubernetes before 3.9.0 contains an argument injection vulnerability in structured tools (kubectl_get, kubectl_describe, kubectl_delete) that allows attackers to bypass the assertNoDangerousFlags security check by supplying resourceType and name parameters with leading dashes. Attackers can inject the --server flag to redirect kubectl commands to an attacker-controlled API server, causing the operator's bearer token to be transmitted externally and enabling full cluster compromise.
Apprise forwards configured auth headers across cross-origin HTTP redirects
Apprise is an open source library which allows you to send a notification to almost all of the most popular notification services available. Prior to 1.11.0, Apprise HTTP-based notification plugins and HTTP attachment and config loaders in apprise/attachment/http.py and apprise/config/http.py follow HTTP redirects by default and resend user-configured auth headers and query parameters on the redirected request, allowing a compromised trusted destination or on-path attacker to receive secrets such as Authorization headers, bearer tokens, custom headers, and service keys. This issue is fixed in version 1.11.0.
PraisonAI before 4.6.78 Code Injection via f-string
PraisonAI versions before 4.6.78 contain a code injection vulnerability in deploy/api.py where the agents_file parameter is directly interpolated into an f-string without sanitization. Attackers can inject arbitrary Python code that executes when the generated server code runs via subprocess.Popen().
PraisonAI Platform before 0.1.9 Authorization Bypass via Dependencies
PraisonAI Platform (praisonai-platform) before 0.1.9 improperly authorizes deletion of issue dependencies. The DELETE dependency route accepts either endpoint of a dependency edge and checks delete permission only against the caller-selected URL issue. A workspace member who cannot delete a dependency through an owner-created issue endpoint (which returns 403) can delete the same dependency edge by targeting a related member-owned issue endpoint, because permission is validated against the member-owned issue's owner. This allows members to bypass owner/admin authorization and remove owner-created issue dependencies.
PraisonAI before 1.6.78 Remote Code Execution via tools.py
PraisonAI (pip package praisonaiagents) before 1.6.78 contains an unsafe dynamic module loading vulnerability in AgentFlow._resolve_pydantic_class (src/praisonai-agents/praisonaiagents/workflows/workflows.py). When a workflow step uses a string output_pydantic reference, the framework locates and imports a sibling tools.py from the workflow file's directory via importlib exec_module without sandboxing, ignoring the PRAISONAI_ALLOW_*_TOOLS environment variables. An attacker who controls a workflow file and its sibling tools.py can execute arbitrary Python code with the workflow runner's privileges when the workflow is executed via WorkflowMana
PraisonAI before 4.6.78 Allowlist Bypass via find -exec
PraisonAI versions before 4.6.78 contain an allowlist bypass vulnerability in shell command execution that allows attackers to execute restricted commands via find's built-in -exec, -execdir, and -delete actions. Attackers can craft find commands with these built-in actions to read blocked files, delete files, or execute non-allowlisted binaries without triggering shell metacharacter filters.
PraisonAI FastContext before 1.6.78 Path Traversal
PraisonAI (praisonaiagents) before 1.6.78 contains a path traversal vulnerability in the FastContext feature (praisonaiagents.context.fast). FastContextAgent.execute_tool() prepends the configured workspace_path only for relative paths and neither rejects absolute paths nor canonicalizes joined paths before enforcing workspace containment. As a result, tool arguments or model-generated function calls to grep_search, glob_search, read_file, or list_directory can supply absolute paths or '../' traversal sequences to read, search, and enumerate files outside the intended workspace directory, with file contents returned to the caller or injected
PraisonAI before 4.6.78 Path Traversal via ContextGatherer
PraisonAI before 4.6.78 contains a path traversal vulnerability in ContextGatherer that fails to validate include paths in .praisoncontext and .praisoninclude files. Attackers can supply absolute paths or parent directory traversal sequences to read arbitrary files outside the workspace and include their contents in the generated context bundle.