PraisonAI Configuration Injection in API Server Generation

PraisonAI before 4.6.78 fails to safely encode deployment configuration values when generating Python source code for API servers. Attackers can inject arbitrary Python expressions through the deploy.api.host and agents_file configuration parameters that execute when the generated server starts or handles requests.

Casky was already ahead

This CVE exploits attack patterns that Casky's 322matched skills already investigate — long before this vulnerability was disclosed. Claude's reasoning model maps these techniques to MITRE ATT&CK, so practitioners who ran these skills have already seen the threat behaviour in their findings.

Analysis

PraisonAI versions before 4.6.78 contain a critical code injection vulnerability where deployment configuration parameters are unsafely incorporated into dynamically generated Python source code. The vulnerability exists in how the platform handles the deploy.api.host and agents_file configuration values—rather than properly encoding these inputs, PraisonAI directly interpolates them into Python code that executes when API servers start or process requests. This allows attackers to inject arbitrary Python expressions that gain execution with the privileges of the running server process. Organizations deploying PraisonAI for AI agent infrastructure are at immediate risk, particularly those accepting configuration from untrusted sources or those with externally-facing deployment pipelines.

Casky's skill mapping identifies this attack pattern through MITRE ATT&CK techniques TA0001 (Initial Access) and TA0043 (Reconnaissance), with 322 mapped security skills detecting the underlying weaknesses. Practitioners using Casky would observe detection signals centered on unsafe code generation patterns—specifically, unsafe string interpolation in dynamically constructed Python source, missing input validation on configuration parameters, and execution of unsanitized user-supplied values in code evaluation contexts. Claude's extended reasoning would correlate configuration injection attempts with suspicious runtime behavior (process spawning, file access, network connections initiated from the API server startup phase). Practitioners would see findings highlighting the contrast between safe configuration encoding practices and PraisonAI's direct parameter injection, enabling rapid identification of vulnerable deployment configurations in their infrastructure before exploitation occurs.

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Casky Risk Score

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EPSS Probability

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Shodan Exposure

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GreyNoise Signal

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Composite risk scoring from EPSS, CISA KEV, Shodan, and GreyNoise — 21 security APIs correlated into a single Casky Risk Score. Coming in Casky Pro. Join early access →

322 Casky skills cover this attack pattern

These skills use Claude AI's reasoning model to surface findings in the same attack categories as CVE-2026-61433.

Abuse of Public-Facing API: Mobile API Abuse

mobile security · low

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abusing-dpapi-for-credential-access

red teaming · high

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abusing-shadow-credentials-for-privesc

red teaming · high

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MITRE ATT&CK Techniques

TA0001 TA0043

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