PraisonAI before 4.6.78 exposes the MCP HTTP-stream transport without authentication by…
CVE-2026-61427 is a high-severity improper input validation vulnerability in PraisonAI from MervinPraison, with a CVSS 3.1 base score of 7.3 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, without any action from a user. The record lists version 4.6.78 as the first without the flaw, so updating PraisonAI to that release or later removes the exposure. There is no confirmed exploitation so far. EPSS estimates a 0.43% chance of exploitation within 30 days, which is low compared with other CVEs.
High severity with no evidence of exploitation so far.
What to do
- Update PraisonAI to 4.6.78 or a later version.
- Read the advisory on github.com for workarounds and exact fixed builds.
- Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| MervinPraison | PraisonAI | before 4.6.78 | 4.6.78 |
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- NetworkCan be exploited remotely over a network, including the internet.
- Attack complexity
- LowNo special conditions are needed; the attack works reliably.
- Privileges required
- NoneNo account or login is needed.
- User interaction
- NoneNo action by a victim is required.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- LowSome restricted data can be read.
- Integrity
- LowLimited modification of data is possible.
- Availability
- LowPerformance or availability is reduced.
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L. Scored by CNA (vulncheck.com).
| Scoring system | Score | Severity | Scored by |
|---|---|---|---|
| CVSS 4.0 | 6.9 | Medium | CNA (vulncheck.com) |
| CVSS 3.1 | 7.3 | High | CNA (vulncheck.com) |
Official description
PraisonAI before 4.6.78 exposes the MCP HTTP-stream transport without authentication by default: the CLI --api-key option defaults to None, and the server only enforces Authorization/Bearer checks when an API key is configured. When an operator runs 'praisonai mcp serve --transport http-stream' without an API key, an unauthenticated client (no Authorization header, and no Origin header, which is also permitted) can initialize a session, enumerate the available tools (tools/list), and invoke tools (tools/call). Additionally, the dispatcher forwards tool-call arguments to handlers without validating them against the advertised inputSchema. The server binds to 127.0.0.1 by default, so remote exploitation requires the operator to bind to a network-accessible address (e.g., --host 0.0.0.0).
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.
How developers prevent this class of flaw
- Consider using language-theoretic security (LangSec) techniques that characterize inputs using a formal language and build recognizers for that language. This effectively requires parsing to be a distinct layer that effectively enforces a boundary between raw input and internal data representations, instead of allowing parser code to be scattered throughout the program, where it could be subject to errors or inconsistencies that create weaknesses.
- Use an input validation framework such as Struts or the OWASP ESAPI Validation API. Note that using a framework does not automatically address all input validation problems; be mindful of weaknesses that could arise from misusing the framework itself (CWE-1173).
- Understand all the potential areas where untrusted inputs can enter the product, including but not limited to: parameters or arguments, cookies, anything read from the network, environment variables, reverse DNS lookups, query results, request headers, URL components, e-mail, files, filenames, databases, and any external systems that provide data to the application. Remember that such inputs may be obtained indirectly through API calls.
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: poc, automatable: yes, technical impact: partial).
- Record last changed materially (score, affected products, status or references).
References
Other vulnerabilities in PraisonAI
- 7.5 High severity
- 8.8 High severity
- 7.8 High severity
- 8.1 High severity
- 8.8 High severity
- 9.8 Critical severity
Recent Improper Input Validation vulnerabilities
- 7.1 High severity
- 9.6 Critical severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 9.0 Critical severity
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