CyberSecBulletin
CVE-2026-30304NVD status: Analyzed

In its design for automatic terminal command execution, AI Code offers two options: Execute…

Published Updated By the CyberSecBulletin desk

CVE-2026-30304 is a critical-severity improper input validation vulnerability in Ai Code from Tianguaduizhang, with a CVSS 3.1 base score of 9.6 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, but only if a user takes part, for example by opening a link or file. Affected Ai Code versions: 3.12.4 and earlier. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.46% chance of exploitation within 30 days, which is low compared with other CVEs.

Patch this week

Critical severity: a successful attack would have severe impact.

What to do

  1. Check which version of Ai Code you run against the affected versions below, and install the vendor's latest release.
  2. Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
  3. Because the attack needs a user to take part, warn users about unexpected links and files related to this product until it is patched.

Affected products and versions

VendorProductAffected versionsFixed in
TianguaduizhangAi Code3.12.4 and earlierNot stated

Version data comes from NVD's product matching. 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
RequiredA user must take an action such as opening a file or link.
Scope
ChangedThe attack can reach beyond the vulnerable component into other systems.
Confidentiality
HighAll data handled by the component can be read.
Integrity
HighData or code can be modified at will.
Availability
HighThe component can be taken down completely.

Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:C/C:H/I:H/A:H. Scored by CISA (ADP).

Official description

In its design for automatic terminal command execution, AI Code offers two options: Execute safe commands and execute all commands. The description for the former states that commands determined by the model to be safe will be automatically executed, whereas if the model judges a command to be potentially destructive, it still requires user approval. However, this design is highly susceptible to prompt injection attacks. An attacker can employ a generic template to wrap any malicious command and mislead the model into misclassifying it as a 'safe' command, thereby bypassing the user approval requirement and resulting in arbitrary command execution.

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.

More Improper Input Validation vulnerabilities (CWE-20)

Timeline

  1. CVE record published.
  2. CISA published its SSVC assessment (exploitation: poc, automatable: no, technical impact: total).
  3. Record last changed materially (score, affected products, status or references).

References

Recent Improper Input Validation vulnerabilities

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