The vast majority of organizations (roughly 77%) have embraced AI in some form, either through active implementation or exploration, according to IBM. This widespread adoption is driven by the potential for increased efficiency and automation in workflows.
However, this growing reliance on AI (particularly advanced models like generative AI and large language models like ChatGPT) necessitates robust security measures. GenAI models, while powerful, are susceptible to manipulation through malicious inputs. Prompt injection vulnerabilities, denial-of-service attacks and overreliance on unverified LLM outputs are just some of the emerging threats. Look at the 2023 outage with OpenAI's AI tool, ChatGPT. The outage was caused by a vulnerability in an open-source library, which may have exposed payment-related information of some customers.
Akto, a provider of API security, knows this. For those unfamiliar with Akto, they specialize in providing solutions to protect APIs from security vulnerabilities. With a team of experts in AI security and a passion for innovation, Akto is committed to enabling organizations to secure their applications from attacks and ensure secure use of GenAI APIs.
Therefore, the company recently launched its GenAI Security Testing solution. This innovative technology positions Akto as a pioneer in offering proactive security testing specifically designed for GenAI models and their APIs.
The solution utilizes advanced techniques to mimic malicious attempts, testing the GenAI API's resilience against unauthorized access, data breaches, and manipulation attempts.
Akto's technology goes beyond traditional security testing by analyzing the specific logic and configurations underlying GenAI models. This uncovers potential security flaws that might remain undetected by conventional methods.
Following a comprehensive analysis, the solution generates detailed reports pinpointing vulnerabilities and offering clear recommendations for patching and strengthening security protocols.
"Often input to an LLM comes from an end-user or the output is shown to the end-user or both. The tests try to exploit LLM vulnerabilities through different encoding methods, separators and markers. This specially detects weak security practices where developers encode the input or put special markers around the input.,” said Ankush Jain, Chief Technology Officer at Akto.io
Unlike traditional security solutions that react to identified threats, Akto's GenAI Security Testing solution takes a proactive stance. By identifying and addressing vulnerabilities before they are exploited, organizations can reduce the risk of data breaches, reputational damage and operational disruptions.
Edited by
Alex Passett
