TCC on macOS isn't just an annoying prompt—it's the last line of defense between malware and your private data. Read this article to learn why.
Lately, I have been reporting many vulnerabilities in third-party applications that allowed for TCC bypass, and I have discovered that most vendors do not understand why they should care. For them, it seems like just an annoying and unnecessary prompt. Even security professionals tasked with vulnerability triage frequently struggle to understand TCC’s role in protecting macOS users’ privacy against malware.
Honestly, I don’t blame them for that because, two years ago, I also didn’t understand the purpose of those “irritating” pop-up notifications. It wasn’t until I started writing malware for macOS. I realized how much trouble an attacker faces because of TCC in actually harming a victim. I wrote this article for Application Developers in mind so that, after reading it, they do not underestimate the vulnerabilities that allow bypassing TCC. It is also intended for Vulnerability Researchers to illustrate an attack vector for further research.
The Bumblebee malware SEO poisoning campaign uncovered earlier this week aimpersonating RVTools is using more typosquatting domainsi mimicking other popular open-source projects to infect devices used by IT staff.
BleepingComputer was able to find two cases leveraging the notoriety of Zenmap, the GUI for the Nmap network scanning tool, and the WinMTR tracerout utility.
Both of these tools are commonly used by IT staff to diagnose or analyze network traffic, requiring administrative privileges for some of the features to work This makes users of these tools prime targets for threat actors looking to breach corporate networks and spread laterally to other devices.
The Bumblebee malware loader has been pushed through at least two domains - zenmap[.]pro and winmtr[.]org. While the latter is currently offline, the former is still online and shows a fake blog page about Zenmap when visited directly.
When users are redirected to zenmap[.]pro from from search results, though, it shows a clone of the legitimate website for the nmap (Network Mapper) utility:
The two sites received traffic through SEO poisoning and rank high in Google and Bing search results for the associated terms.
Bleepingcolputer's tests show that if you visit the fake Zenmap site directly, it shows several AI-generated articles instead, as seen in the image below:
The payloads delivered through the download section ‘zenmap-7.97.msi’ and ‘WinMTR.msi, and they both evade detection from most antivirus engines on VirusTotal [1, 2].
The installers deliver the promised application along with a malicious DLL, as in the case of RVTools, which drops a Bumblebee loader on users' devices.
From there, the backdoor can be used to profile the victim and introduce additional payloads, which may include infostealers, ransomware, and other types of malware.
Apart from the open-source tools mentioned above, BleepingComputer has also seen the same campaign targeting users looking for Hanwha security camera management software WisenetViewer.
Cyjax’s researcher Joe Wrieden also spotted a trojanized version of the video management software Milestone XProtect being part of the same campaign, the malicious installers being delivered ‘milestonesys[.]org’ (online).
Welcome to our OCPL Fellows Feature series, brought to you by our current cohort of talented researchers. These pieces explore key challenges at the intersection of U.S.-China and global emerging technology competition.
Massive leaks of information stored in government-owned databases have become increasingly common in China throughout the 2020s.
Chinese hacktivists likely executed some of these leaks to call attention to the scope and pervasiveness of state surveillance.
Hackers in China have previously been prevented from organizing into groups and carrying out both nationalist and apolitical hacking. It is plausible that hackers would have little to lose by pivoting to hack to express dissent.
Introduction
What comes to mind when you think about data protection? Perhaps the right to privacy or cybersecurity, but almost certainly not “streaking.” However, Chinese netizens commonly use this term (裸奔, luǒbēn) to describe the sense of embarrassment an individual feels when their personal data has been unintentionally exposed. The use (and censorship) of this phrase has only increased as large-scale data leaks have risen dramatically in China throughout the 2020s.
When these data leaks occur, commentary is quickly taken down to prevent Chinese internet users from uncovering the scope of state surveillance practices. That’s partly because retrospective analysis of these incidents often reveals that they resulted directly from Chinese government bodies’ lax data management practices. These incidents have proved shameful for party leaders; while not directly acknowledging these leaks, high-ranking officials like the late Li Keqiang call for heightened “information security” standards in their aftermath.
Over the past year, Phishguard observed an increase in phishing campaigns leveraging Scalable Vector Graphics (SVG) files as initial delivery vectors, with attackers favoring this format due to its flexibility and the challenges it presents for static detection.
SVGs are an XML-based format designed for rendering two-dimensional vector graphics. Unlike raster formats like JPEGs or PNGs, which rely on pixel data, SVGs define graphics using vector paths and mathematical equations, making them infinitely scalable without loss of quality. Their markup-based structure also means they can be easily searched, indexed, and compressed, making them a popular choice in modern web applications.
However, the same features that make SVGs attractive to developers also make them a highly flexible - and dangerous - attack vector when abused. Since SVGs are essentially code, they can embed JavaScript and interact with the Document Object Model (DOM). When rendered in a browser, they aren’t just images - they become active content, capable of executing scripts and other manipulative behavior. In other words, SVGs are more than just static images; they are also programmable documents.
The security risk is underestimated, with SVGs frequently misclassified as innocuous image files, similar to PNGs or JPEGs - a misconception that downplays the fact that they can contain scripts and active content. Many security solutions and email filters fail to deeply inspect SVG content beyond basic MIME-type checks (a tool that identifies the type of a file based on its contents), allowing malicious SVG attachments to bypass detection.
We’ve seen a rise in the use of crafted SVG files in phishing campaigns. These attacks typically fall into three categories:
Redirectors - SVGs that embed JavaScript to automatically redirect users to credential harvesting sites when viewed
Self-contained phishing pages - SVGs that contain full phishing pages encoded in Base64, rendering fake login portals entirely client-side
DOM injection & script abuse - SVGs embedded into trusted apps or portals that exploit poor sanitisation and weak Content Security Policies (CSPs), enabling them to run malicious code, hijack inputs, or exfiltrate sensitive data
Given the capabilities highlighted above, attackers can now use SVGs to:
Gain unauthorized access to accounts
Create hidden mail rules
Phish internal contacts
Steal sensitive data
Initiate fraudulent transactions
Maintain long-term access
Our telemetry shows that manufacturing and industrial sectors are taking the brunt of these SVG-based phishing attempts, contributing to over half of all targeting observed. Financial services follow closely behind, likely due to SVG’s ability to easily facilitate the theft of banking credentials and other sensitive data. The pattern is clear: attackers are concentrating on business sectors that handle high volumes of documents or frequently interact with third parties.
AhnLab SEcurity intelligence Center (ASEC) recently identified a phishing malware being distributed in Scalable Vector Graphics (SVG) format. SVG is an XML-based vector image file format commonly used for icons, logos, charts, and graphs, and it allows the use of CSS and JS scripts within the code. In November 2024, the ASEC Blog introduced SVG […]
In this post I’ll show you how I found a zeroday vulnerability in the Linux kernel using OpenAI’s o3 model. I found the vulnerability with nothing more complicated than the o3 API – no scaffolding, no agentic frameworks, no tool use.
Recently I’ve been auditing ksmbd for vulnerabilities. ksmbd is “a linux kernel server which implements SMB3 protocol in kernel space for sharing files over network.“. I started this project specifically to take a break from LLM-related tool development but after the release of o3 I couldn’t resist using the bugs I had found in ksmbd as a quick benchmark of o3’s capabilities. In a future post I’ll discuss o3’s performance across all of those bugs, but here we’ll focus on how o3 found a zeroday vulnerability during my benchmarking. The vulnerability it found is CVE-2025-37899 (fix here), a use-after-free in the handler for the SMB ‘logoff’ command. Understanding the vulnerability requires reasoning about concurrent connections to the server, and how they may share various objects in specific circumstances. o3 was able to comprehend this and spot a location where a particular object that is not referenced counted is freed while still being accessible by another thread. As far as I’m aware, this is the first public discussion of a vulnerability of that nature being found by a LLM.
Before I get into the technical details, the main takeaway from this post is this: with o3 LLMs have made a leap forward in their ability to reason about code, and if you work in vulnerability research you should start paying close attention. If you’re an expert-level vulnerability researcher or exploit developer the machines aren’t about to replace you. In fact, it is quite the opposite: they are now at a stage where they can make you significantly more efficient and effective. If you have a problem that can be represented in fewer than 10k lines of code there is a reasonable chance o3 can either solve it, or help you solve it.
Benchmarking o3 using CVE-2025-37778
Lets first discuss CVE-2025-37778, a vulnerability that I found manually and which I was using as a benchmark for o3’s capabilities when it found the zeroday, CVE-2025-37899.
CVE-2025-37778 is a use-after-free vulnerability. The issue occurs during the Kerberos authentication path when handling a “session setup” request from a remote client. To save us referring to CVE numbers, I will refer to this vulnerability as the “kerberos authentication vulnerability“.
