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Chainlit AI Framework Flaws Enable Data Theft via File Read and SSRF Bugs

Security vulnerabilities were uncovered in the popular open-source artificial intelligence (AI) framework Chainlit that could allow attackers to steal sensitive data, which may allow for lateral movement within a susceptible organization.

Zafran Security said the high-severity flaws, collectively dubbed ChainLeak, could be abused to leak cloud environment API keys and steal sensitive files, or perform server-side request forgery (SSRF) attacks against servers hosting AI applications.

Chainlit is a framework for creating conversational chatbots. According to statistics shared by the Python Software Foundation, the package has been downloaded over 220,000 times over the past week. It has attracted a total of 7.3 million downloads to date.

Zendesk ticket systems hijacked in massive global spam wave

People worldwide are being targeted by a massive spam wave originating from unsecured Zendesk support systems, with victims reporting receiving hundreds of emails with strange and sometimes alarming subject lines.

The wave of spam messages started on January 18th, with people reporting on social media that they received hundreds of emails.

While the messages do not appear to contain malicious links or obvious phishing attempts, the sheer volume and chaotic nature of the emails have made them highly confusing and potentially alarming for recipients.

New Android malware uses AI to click on hidden browser ads

A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact with specific advertisement elements.

The mechanism relies on visual analysis based on machine learning instead of predefined JavaScript click routines, and does not involve script-based DOM-level interaction like classic click-fraud trojans.

The threat actor is using TensorFlow.js, an open-source library developed by Google for training and deploying machine learning models in JavaScript. It permits running AI models in browsers or on servers using Node.js.

VoidLink cloud malware shows clear signs of being AI-generated

The recently discovered cloud-focused VoidLink malware framework is believed to have been developed by a single person with the help of an artificial intelligence model.

Check Point Research published details about VoidLink last week, describing it as an advanced Linux malware framework that offers custom loaders, implants, rootkit modules for evasion, and dozens of plugins that expand its functionality.

The researchers highlighted the malware framework’s sophistication, assessing that it was likely the product of Chinese developers “with strong proficiency across multiple programming languages.”

Black Basta Ransomware Leader Added to EU Most Wanted and INTERPOL Red Notice

Ukrainian and German law enforcement authorities have identified two Ukrainians suspected of working for the Russia-linked ransomware-as-a-service (RaaS) group Black Basta.

In addition, the group’s alleged leader, a 35-year-old Russian national named Oleg Evgenievich Nefedov (Нефедов Олег Евгеньевич), has been added to the European Union’s Most Wanted and INTERPOL’s Red Notice lists, authorities noted.

“According to the investigation, the suspects specialized in technical hacking of protected systems and were involved in preparing cyberattacks using ransomware,” the Cyber Police of Ukraine said in a statement.

Ingram Micro says ransomware attack affected 42,000 people

Information technology giant Ingram Micro has revealed that a ransomware attack on its systems in July 2025 led to a data breach affecting over 42,000 individuals.

Ingram Micro, one of the world’s largest business-to-business service providers and technology distributors, has over 23,500 associates, more than 161,000 customers, and reported net sales of $48 billion in 2024.

In data breach notification letters filed with Maine’s Attorney General and sent to those affected by the incident, the company said the attackers stole documents containing a wide range of personal information, including Social Security numbers.

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