CVE-2012-5958Patch(libupnp_project / libupnp)

Can open source models be useful in cybersecurity? A few months ago, with the help of AI I discovered that my old TV was susceptible to a Linux bug, CVE-2012-5958, and I used that to hack the TV. The catch? I'm now using Deepseek V4 Pro to see if open source models are capable of finding the exact same bug, because the earlier closed models I used for this research now blatantly refuse to work on my own codebase. In this video I share the short story behind the TV, a brief look at the bug itself, and why we should actually care about this increase in capabilities -- because this same bug could be present in more than just televisions, like routers, cameras, and possibly even medical devices running that version of Linux. DeepSeek has not quite cracked the case yet, however, I suspect that may be a harness / tooling issue rather than a model capability issue as the model was able to autonomously test the capabilities of the TV for over an hour with minimal input required from my end, which shows me it's clearly capable, it just needs to be steered correctly. So, are open source models useful in cybersecurity? Increasingly yes, in just a short amount of time they went from ok to autonomous research over the span of hours. These capabilities will only increase over time, and it's important we address it. This puts the same tools in the hands of the people defending their own devices (as we don't need to be reliant on just the big labs for this). Also next time, I'll have a better camera!

13 years after CVE-2012-5958 was published, Claude Code helped crash a smart TV with one crafted UDP packet. That matters more when you put it beside Google's Antigravity patch. Pillar Security found a prompt-injection path where the find_by_name native tool ran before Secure Mode could inspect it, creating a sandbox escape and remote code execution path. Same lesson, different surfaces. AI did not invent the old UPnP library bug. Antigravity did not fail because agents are magic. Both cases show control boundaries moving to the wrapper layer: what the agent can see, what native tools can execute, and how much forgotten infrastructure it can rediscover. I suspect 2026's security debt will look less like one spectacular zero-day and more like agents making old assumptions executable again. Sources: https://nvd.nist.gov/vuln/detail/cve-2012-5958 https://cyberscoop.com/google-antigravity-pillar-security-agent-sandbox-escape-remote-code-execution/