GHSA-h2w2-v7j6-xqm4
HIGHGHSA-h2w2-v7j6-xqm4 is a high-severity (CVSS 8.8) CWE-693 vulnerability in praisonai. O3 Security confirms whether GHSA-h2w2-v7j6-xqm4 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.
npm PraisonAI AgentLoop onToolCall approval runs after tool execution
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
- A successful exploit gives an attacker total control of the affected component, not partial access.
Exploitation and automatability from CISA’s SSVC triage for GHSA-h2w2-v7j6-xqm4.
Real-World Exposure
How broadly this vulnerability is actually deployed: weekly install volume shows current usage, and reverse-dependency count shows how many other packages break if it stays unpatched.
praisonainpmDescription
Summary
The published npm package praisonai exports createAgentLoop(), whose onToolCall callback is documented and exampled as an approval hook. The implementation calls PraisonAI's generateText() wrapper with the caller's executable tools first, receives toolResults, and only then calls onToolCall().
Because AI SDK generateText() executes tools with an execute function as part of the generation call, onToolCall can deny a tool only after the sensitive side effect has already happened. PraisonAI then returns finishReason: "tool_rejected", which is a false security signal: the rejected tool already ran.
The PoV is deterministic and local-only. It uses mock AI SDK modules, no live model call, no API key, and no network target. The tool increments an in-memory counter rather than touching the filesystem or executing commands.
Technical Details
In src/praisonai-ts/src/ai/agent-loop.ts, the public config says:
/** On tool call callback (for approval) */
onToolCall?: (toolCall: ToolCallInfo) => Promise<boolean>;
The inline approval example also asks a user for approval and returns the decision:
onToolCall: async (toolCall) => {
const approved = await askUserForApproval(toolCall);
return approved;
}
However, AgentLoop.step() calls generateText() with the executable tools before invoking onToolCall:
const result = await generateText({
model: this.config.model,
messages: this.messages as any,
tools: this.config.tools,
maxSteps: 1,
});
It then materializes toolResults:
toolResults: result.toolResults.map(tr => ({
toolCallId: tr.toolCallId,
toolName: tr.toolName,
result: tr.result,
})),
Only afterward does the approval callback run:
if (this.config.onToolCall) {
for (const toolCall of step.toolCalls) {
const approved = await this.config.onToolCall(toolCall);
if (!approved) {
this.complete = true;
step.finishReason = 'tool_rejected';
break;
}
}
}
src/praisonai-ts/src/ai/generate-text.ts forwards the caller's tools directly to AI SDK:
const result = await sdk.generateText({
model,
...
tools: options.tools,
maxSteps: options.maxSteps,
...
});
AI SDK documents that generateText() "generates text and calls tools", and that tools with an execute function run automatically unless approval is handled before execution with needsApproval.
The published npm:[email protected] dist files preserve the same order:
dist/ai/agent-loop.jslines 150-157 callgenerateText()with executable tools.- lines 162-171 materialize
toolResults. - lines 183-195 call
onToolCall()and settool_rejectedafterward.
Why This Is Not Intended Behavior
This is not a trust-model-only issue. PraisonAI explicitly labels onToolCall as an approval callback and shows an approval example. A user who returns false from that callback expects the tool not to run.
It also conflicts with the AI SDK execution model PraisonAI wraps:
- AI SDK
generateText()executes tools that include anexecutefunction. - AI SDK approval is a pre-execution boundary (
needsApproval), not a post-execution notification. - AI SDK loop control documentation treats "a tool call needs approval" as a condition that stops or pauses the loop before executing the tool.
PraisonAI's current behavior instead creates a post-execution audit hook while naming and documenting it as approval.
PoV
Run from a local reproduction checkout:
node poc/pov_poc.js 1.7.1
Expected output includes:
{
"praisonaiVersion": "1.7.1",
"createAgentLoopExported": true,
"eventOrder": ["tool-executed", "approval-denied"],
"sideEffects": 1,
"finishReason": "tool_rejected",
"toolCallCount": 1,
"toolResultCount": 1,
"rejectedAfterExecution": true,
"vulnerable": true,
"patchedControl": {
"order": ["approval-denied"],
"sideEffects": 0,
"toolCallCount": 1,
"toolResultCount": 0,
"blocksBeforeExecution": true
}
}
The PoV installs npm:[email protected] into a temporary project and supplies mock ai and @ai-sdk/openai modules. The mocked generateText() returns one tool-call intent and executes a supplied execute handler if present. This keeps the proof deterministic and isolates PraisonAI's ordering bug.
The vulnerable run uses createAgentLoop() with:
- a
dangerousWritetool whoseexecute()handler increments an in-memory side-effect counter and recordstool-executed; - an
onToolCallapproval callback that always returnsfalseand recordsapproval-denied.
The observed order is:
tool-executed > approval-denied
That proves denial happens after execution. The toolResults array contains the tool's result even though PraisonAI reports finishReason: "tool_rejected".
The patched-control comparison strips executable handlers before the model step, requests approval on the tool-call intent, and only executes if approval succeeds. With the same denial decision, the control output is:
approval-denied
sideEffects = 0
toolResultCount = 0
PoC
The PoV section above contains the local reproduction command, input, and decisive output.
Impact
Any application using npm PraisonAI createAgentLoop() with onToolCall as a human-in-the-loop or policy approval boundary can execute denied tools.
If the application exposes the agent loop to lower-trust prompts or users and registers powerful tools, an attacker can cause the model to call a tool that the approval callback denies. The denial occurs too late. Depending on the registered tool, impact can include file modification, command execution, external API calls, data mutation, credential use, or other side effects with the privileges of the PraisonAI process.
The report does not claim that npm PraisonAI exposes this as a default network service. It is a library-level approval-boundary bypass in the exported TypeScript agent-loop API.
Severity
Suggested severity: High.
Rationale:
AV: common deployment pattern is an application exposing agent prompts over a network.AC: attacker only needs to induce a tool call.PR: conservative base score assumes the attacker can submit prompts to the application.UI: no additional operator action is needed for the tool to execute before denial; even a denial callback is too late.S: impact is in the PraisonAI-hosting application process.C/I/A: depends on registered tools; shell/file/API tools can affect confidentiality, integrity, and availability.
If maintainers score only local scripts that process untrusted repositories or prompts, AV:L may be reasonable. If they score public unauthenticated prompt endpoints built on this API, PR:N may be reasonable.
Suggested Fix
Do not pass executable tool handlers into generateText() before approval.
One safe shape:
- Convert configured tools into intent-only tool definitions without
execute. - Call
generateText()to obtain the model's tool-call intent. - Invoke
onToolCall(toolCall)before any side effect. - Execute the selected tool only if approval returns true.
- Append approved tool results to the conversation and continue the loop.
Alternatively, if PraisonAI wants to delegate approval to AI SDK v6, translate onToolCall into per-tool needsApproval semantics so AI SDK pauses before calling execute.
Regression tests should include:
onToolCallreturns false and the toolexecute()counter remains zero;onToolCallreturns true and the tool executes exactly once;tool_rejectedis never reported together with a tool result produced by the denied tool;- streaming and non-streaming loop variants use the same approval ordering if added later.
Affected Package/Versions
- Repository:
MervinPraison/PraisonAI - Package:
npm:praisonai - Component: TypeScript
AgentLoop - Current head validated:
1ad58ca02975ff1398efeda694ea2ab78f20cf3e - Current tag validated:
v4.6.58 - Latest npm package validated:
1.7.1
Suggested affected range:
npm:praisonai >= 1.4.0, <= 1.7.1
Selected version sweep:
1.0.0: package main cannot be required in the selected test environment.1.2.0:createAgentLoopis not exported.1.3.6:createAgentLoopis not exported.1.4.0: vulnerable.1.5.0: vulnerable.1.5.4: vulnerable.1.6.0: vulnerable.1.7.0: vulnerable.1.7.1: vulnerable.
Advisory History
This is distinct from known and previously submitted PraisonAI issues:
GHSA-ffp3-3562-8cv3covers Pythonpraisonaiagentsapproval cache keyed by tool name rather than invocation arguments.GHSA-qwgj-rrpj-75xmcovers Python Chainlit UI overriding configured approval mode withauto.GHSA-63v4-w882-g4x2/ poc covers PythonHTTPApprovalapproval-page XSS.- poc covers npm TypeScript
AgentOSmissing authentication. - poc covers npm TypeScript
codeModesandbox escape. - poc covers npm TypeScript
MCPServermissing authentication.
No visible local or GitHub advisory covers npm TypeScript AgentLoop.onToolCall executing after tool results already exist.
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 📦npm | praisonai | ≥ 1.4.0&&< 1.7.2 | 1.7.2 |
Detection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for praisonai. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.
Fix
Update praisonai to 1.7.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-h2w2-v7j6-xqm4 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
How O3 protects you
O3 pinpoints whether GHSA-h2w2-v7j6-xqm4 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.
Tailored to GHSA-h2w2-v7j6-xqm4. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-h2w2-v7j6-xqm4 in your dependencies?
O3 detects GHSA-h2w2-v7j6-xqm4 across npm dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.