{"id":99663,"date":"2026-07-14T10:33:48","date_gmt":"2026-07-14T10:33:48","guid":{"rendered":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/?post_type=the-hub&p=99663"},"modified":"2026-07-15T09:10:15","modified_gmt":"2026-07-15T09:10:15","slug":"veracityai-penetration-testing","status":"publish","type":"the-hub","link":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/the-hub\/veracityai-penetration-testing\/","title":{"rendered":"VeracityAI Penetration Testing"},"content":{"rendered":"

AI penetration testing assesses AI and LLM systems for security weaknesses. Like traditional penetration testing, the goal is to identify vulnerabilities before an attacker does. The difference is in what\u2019s being tested and how those systems behave.<\/p>\n

With AI, the focus shifts away from misconfigurations or unpatched software. Instead, testing looks at how a model responds to inputs, what data it can access, and whether it can be manipulated into acting outside its intended boundaries.<\/p>\n

This distinction is crucial, and it\u2019s why a typical web application penetration test won\u2019t fully cover AI-specific risks.
\nTests built for web applications are likely to miss vectors like prompt injection attacks and Retrieval-Augmented Generation (RAG) pipeline poisoning.<\/p>\n

That said, web app penetration testing isn\u2019t being replaced. Each test addresses specific areas and requires its own methodology and expertise. Used together, they provide broader coverage and help ensure the entire application stack is resilient to modern threats. It\u2019s also worth distinguishing between AI systems and LLMs, as they require different testing approaches:<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>

AI refers to the end-to-end solution:<\/h2>\n

This includes models, data, integrations, and automated
\nworkflows. Security concerns arise from system behavior,
\nwhere attackers exploit or manipulate how the solution
\ninteracts with data and external systems.<\/p>\n

LLMs are the core decision
\n-making component:<\/h2>\n

The LLM is responsible for generating language-based
\noutputs, so testing looks at those responses, including
\naccuracy, data exposure and policy adherence.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

<\/div>\"\"<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>
<\/div>\"\"<\/div><\/div><\/div><\/div><\/div>

AI refers to the end-to-end solution:<\/h2>\n

This includes models, data, integrations, and automated
\nworkflows. Security concerns arise from system behavior,
\nwhere attackers exploit or manipulate how the solution
\ninteracts with data and external systems.<\/p>\n

LLMs are the core decision
\n-making component:<\/h2>\n

The LLM is responsible for generating language-based
\noutputs, so testing looks at those responses, including
\naccuracy, data exposure and policy adherence.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>\n","protected":false},"featured_media":99646,"parent":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-99663","the-hub","type-the-hub","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/wp-json\/wp\/v2\/the-hub\/99663","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/wp-json\/wp\/v2\/the-hub"}],"about":[{"href":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/wp-json\/wp\/v2\/types\/the-hub"}],"version-history":[{"count":6,"href":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/wp-json\/wp\/v2\/the-hub\/99663\/revisions"}],"predecessor-version":[{"id":99736,"href":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/wp-json\/wp\/v2\/the-hub\/99663\/revisions\/99736"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/wp-json\/wp\/v2\/media\/99646"}],"wp:attachment":[{"href":"https:\/\/darraghkerrigancreative.ie\/veractyai2\/wp-json\/wp\/v2\/media?parent=99663"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}