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    Home»Security»AI coding assistants increase deep cyber security risks
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    AI coding assistants increase deep cyber security risks

    PineapplesUpdateBy PineapplesUpdateSeptember 25, 2025No Comments2 Mins Read
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    AI coding assistants increase deep cyber security risks
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    AI coding assistants increase deep cyber security risks

    Timsah of i-Gentic AI says, “The bridge requests associated with the codes generated should always be reviewed by experienced engineers, who understand the code, business logic and compliance references.” “Organizations should also give priority to transparency and lineage by treating AI-writer code like any other third-party dependence.”

    Timsah says: “They require complete traceability to write it, which model produced it, and under which parameters, which makes it easy to overcome audit and issues later.”

    Mitigation strategies

    AI coding can be a force multiplier for supporting support development teams, but only when enterprise manufactures railings to manage the risk related risks.

    “With strong governance, automated oversight and human accountability organizations can exploit the speed of AI without multiplying weaknesses,” I-Jentic AI’s Timsah recommends.

    Other experts made recommendations on reducing the risks associated with AI coding assistants:

    • For example, by taking advantage of the MCP (model reference protocol) server, integrate safety tooling in AI code assistants.
    • Limit the amount of AI-related changes based on the project so that the bridge requests remain manageable.
    • Strictly enable automatic checks in CI/CD – secret scanner, static analysis and cloud configuration control.

    The mitigation of flaws created by AI coding assistants requires a different mentality, called Timsah of I-Jentic AI.

    He argued, “Enterprises should use AI to look at AI to AI that is deploying agent AI solutions that automatically scan the AI-Janit code against regulatory requirements before policies, safety standards and codes are merged,” they argue.

    Enterprises should also adopt shift-left security and continuous monitoring.

    “The security check cannot be bolt at the end of the pipeline,” says Timsah. “They should be directly integrated into CI/CD procedures so that the AI-related code obtains the same inquiry as the open-source contribution.”

    Pineest’s Rylko says: “We consider AI assistants as ‘junior developers’ – their code is always tested by seniors.”

    assistants coding Cyber deep Increase risks Security
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