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Tsec16 retweeted
We burned 11.7bn tokens to find the best cyber AI model aikido.dev/blog/ai-model-ben…
Tsec16 retweeted
We just released our uncensored weights for Qwen3.8 27B FP8, designed for AI Red Teaming and security research, enjoy!
huggingface.co/orcarouter/Qw…
Tsec16 retweeted
I've praised a few malwares for various reasons. However, this particular malware is very interesting.
- Initially masquerading malware, designed to target very specific audience
- Written in multiple programming languages. However, the first stage is written in an uncommon programming language (Delphi) and compiled using an uncommon compiler (Embarcadero), specifically Delphi GUI TForm from Embarcadero (Vcl?)
- Obfuscated, in a very natural way. The binary at first glance appears semi-legitimate, it hides itself well
- The first stage (stager, or packer) contains multiple layers of decoy data. It makes reverse engineering challenging, not due to difficulty but time exhaustion
- Secondary stage (where I'm currently at) is loaded into memory discretely, it flows naturally with the GUI application. When decompiled, the stager has over 15,000 functions. It makes finding the in-memory loaded secondary stage tricky
- The secondary stage has some form of interprocess communication, it relies on the first stage to load it. If the first stage is not present, it does not work.
- The second stage works (in a currently unknown capacity) to load a third stage payload. However, the secondary stage with the first stage work (in a currently unknown way) to decrypt the third (and potentially final) stage a/k/a the actual payload
- The second stage uses deterministic probability to alert the first stage if the machine executing the first stage is a virtual machine and/or anti malware environment.
- The second stage has multiple integrity checks, it ensures it has not been tampered with to force the binary to pull the third and final stage.
This malware is pretty tricky. It definitely hasn't been written by a noob. This is definitely a very skilled Threat Actor who is using AI to supercharge their code base. Based on my conversations with my colleague, and information he can share, this code base has been rapidly evolving over the past couple of months in a uncharacteristic manner. While this Threat Actor has always shown evolution and improvement, it is now much faster, precise, and flexible.
Overall, based on what I've seen so far, they've put in a lot of work to make this as painful as possible. In order to successfully reverse engineer this binary, it require outside the box thinking and/or building a custom solution to successfully trick the secondary stager to give up the goop (the third stage)... or a custom extractor to pull the third stage statically.
No solution is ideal. This is good malware. If it's not state-sponsored, it's someone who has been doing this a long time and knows ball.
Replying to @vxunderground
I don't remember the last time you praised a malware this much, it's been a while since we got those malware ratings, also can you like share the file hash/ malware itself for us newbies to take a bite at it and see what it does and how it works?
Or is it already up on the site?
Tsec16 retweeted
The independent @ArtificialAnlys Benchmark confirms Kimi K3's performance.
Furthermore, the weights will be released soon as well.
We have an open-source, open-weight model that is overall better than Opus 4.8 and comes from China.
Just let that sink in for a while. I'm serious: the entire game has changed. I expect this will trigger some code red for some.
And the next GLM is already in the starting blocks.
Kimi K3 may be the DeepSeek 2.0 moment. The benchmark results are out, and they are outstanding. And they proof one thing very clearly.
I believe this is the DeepSeek 2.0 moment. Does that sound like an exaggeration? At first glance, perhaps. The benchmarks still need to prove themselves in real-world use. But one thing already seems clear: Kimi K3 is ahead of Opus 4.8 and, broadly speaking, just behind GPT-5.6 and Fable 5.
Opus 4.8 was released at the end of May, specifically on May 26, roughly a month and a half ago. Kimi K3 generally outperforms Opus 4.8. That effectively disproves the claim that Chinese open source models consistently trail US closed source models by six to eight months.
Of course, most users will continue to choose the very best model available, and I do not expect millions of people to cancel their ChatGPT subscriptions overnight. However, Kimi K3 makes one thing abundantly clear: the US lead is continuing to shrink. Despite sanctions, Chinese AI labs are succeeding in training increasingly capable models. Whether reinforcement learning or distillation is the primary reason, I cannot say. But Kimi K3 demonstrates to the world that a turning point may be approaching. China is steadily moving toward technological parity. The statement by the founder of Zhipu AI should also attract attention: the company says it plans to release a GLM model in the Mythos class by the end of the year.
Kimi K3 is not Fable, and it is not Mythos. But it is already very close to the leading Western state-of-the-art models. That is highly significant.
Tsec16 retweeted
NTLM Reflection Attack
🔥 Telegram: t.me/hackinarticles
✴ Twitter: teapaw.org/hackinarticles
NTLM Reflection is a technique where attackers trick a system into authenticating against itself, allowing privilege escalation without knowing user credentials.
⚡ Attack Highlights
🎯 Coerce victim machine to authenticate
🔄 Reflect NTLM challenge back to same system
🎟 Reuse authentication response
🔐 Gain authenticated session as victim
🚀 Escalate privileges to SYSTEM
💡 Reflection attacks exploit flaws in challenge-response authentication, where a system unknowingly validates its own authentication request.
📖 Article: hackingarticles.in/ntlm-refl…
#CyberSecurity #ActiveDirectory #NTLM #RedTeam #Pentesting #PrivilegeEscalation #InfoSec
Tsec16 retweeted
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Tsec16 retweeted
Mustang Panda Uses Zoho WorkDrive as Command Channel in Indian Government Attacks thehackernews.com/2026/06/mu…
Tsec16 retweeted
Kick off Hacker Summer 2026 with an ACPT Bootcamp Giveaway!
The ACPT Bootcamp begins on 3 July 2026, and one lucky winner will receive a FREE seat as part of our Pre-Hacker Summer Celebration.
Designed for aspiring penetration testers, the 4-week hands-on ACPT Bootcamp covers enterprise infrastructure attacks using NetExec, Active Directory, Linux & Windows privilege escalation, network pivoting, AD CS abuse, and more.
How to enter:
• Like this post and follow @AlteredSecurity
• Comment why you'd like to attend the ACPT Bootcamp
• Repost this post
Winners will be selected at random and announced on June 30, 2026.
Learn more:
alteredsecurity.com/acpt-boo…
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heavener: This is what happens when you can't afford EDR licenses by otter.
TLDR; A modular engine that runs real vendor detection logic from reverse-engineered EDR components against live or replayed Windows telemetry.
Blog:- blog.otterpwn.com/projects/h…
#edr #detection
1/ We are sharing additional details regarding our investigation into unauthorized access to GitHub's internal repositories.
Yesterday we detected and contained a compromise of an employee device involving a poisoned VS Code extension. We removed the malicious extension version, isolated the endpoint, and began incident response immediately.
Tsec16 retweeted
MOST COMPLETE CLAUDE CODE SETUP OPEN SOURCED
- 27 agents, 64 skills, 33 commands + built-in AgentShield with 1,282 security tests
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- Works on Cursor, OpenCode, Codex CLI — one repo replaces weeks of setup, 100% free/open-source
Repo: github.com/affaan-m/everythi…
Tsec16 retweeted
Every Sliver C2 Tutorial Was Outdated. So I Wrote My Own medium.com/@aviraj3868/every…
Tsec16 retweeted
AV/EDR Lab Environment Setup
A curated list of various resources helpful in building own malware-centric research lab.
A post by Udayveer Singh (@m4lici0u5)
Source: an0nud4y.notion.site/AV-EDR-…
#redteam #blueteam #maldev #malwaredevelopment
Tsec16 retweeted
Dumping LSASS is old school. If an admin is connected on a server you are local admin on, just create a scheduled task asking for a certificate on his behalf, get the cert, get its privs. All automatized in the schtask_as module for NetExec 🥳🥳🥳
Tsec16 retweeted
This is what we're up against if we allow AI vibe coding to go unsupervised.
Strong proof that LLM-generated code can cause more harm than good in unskilled hands.
I stand by 100% of the points in this post.
Hiring software developers is going to become a much bigger pain than it used to be, since recruiters cannot make a justified decision just by glancing at their GitHub profile.
Open-source projects will be harder to manage due to the higher costs of reviewing PRs to prune AI slop.
This is probably the best quote from the post that sums it all up:
"AI multiplies what you already know.
- 10 years of experience × AI = 10x output
- 0 years of experience × AI = 10x slop"
The skill is not yet dead.
webmatrices.com/post/vibe-co…







































