Justin J Williams retweeted
Good news everyone!
The absolute legends @ the Sury php mirror have backported the patch all the way back to 5.6
Justin J Williams retweeted
🚨 Nightmare day for cybersecurity
Multiple major security incidents, active exploits, supply chain compromises...
If you run production systems, start patching NOW.
PHP: Two critical unauthenticated RCEs. Attackers already exploiting them. Patch NOW
LiteLLM: v1.107.0 on PyPI and Docker is BACKDOORED. Steals cloud, SSH, and AI credentials. Pin 1.106.2. Rotate secrets.
eMudhra: A certificate authority's keys were crackable. Update your browsers, systems, and trust stores.
Node.js / Next.js / React: Security releases for Brotli RCE, TLS bypasses, and TWO critical Next.js RCEs.
TiDB Cloud: PingCAP breached through stolen credentials. Customer information and other sensitive data exfiltrated. Read the attacker's release, fun stuff.
Plex2Shell: Weaponized within HOURS of the PoC. Attackers already deploying cryptominers and proxy backdoors.
BeyondTrust / Ivanti: Actively exploited zero-days added to CISA's KEV catalog. BeyondTrust attacks linked to a China-nexus campaign.
And that's not even the full list.
Patch. Audit. Rotate. NOW.
Justin J Williams retweeted
Yes!!!!!!!.. added to test queue
Google just open-sourced Harness².
(turn any harness into a self-improving system)
a harness is everything wrapped around the model, like the system prompt, tools, memory, skills, and subagents. today a person designs it once, and the agent runs every new task with that same fixed setup.
Harness² lets the agent refine that setup for each new task on its own, with the model weights left untouched.
on every task, the agent proposes edits to its harness, runs a few candidate versions, and composes a better harness by comparing how those runs behaved.
because it learns from the differences between runs, it needs no correct answer or grader for the task.
that covers a single task. Harness² also carries what it learns from one task into the next.
after each task, it saves the harness it settled on along with the lessons that held up across the runs. the next time it refines a harness, it starts from those notes instead of from scratch.
this means every finished task makes the next round of edits more informed.
Google tested this with Gemini 3.5 Flash and GLM-5 on legal, office, and professional work benchmarks. one round of edits was enough to beat their original harnesses, and giving the agent more rounds pushed scores higher.
those extra rounds can go wide or deep. the agent either tries several candidate harnesses at once or keeps refining a single one step by step, using OpenCode or Codex to carry out the work.
you can find the Harness² repo here: github.com/google-research/h…
I wrote about a similar idea for agents already running in production, where the harness should repair itself after a failure instead of waiting for someone to debug the trace by hand.
that piece walks through how @Cometml's Opik (open-source) closes this loop, going from a failing trace to a proposed fix to a regression test that stops the same failure from coming back. it's quoted below.
Justin J Williams retweeted
Run DeepSeek V4.1 Flash 1037 on 3/4 DGX Sparks 🔥
This uses the original quant posted by DeepSeek, on both 3 and 4x Sparks. No further quantization was made.
4x DGX Sparks:
- 87 tok/s on prose, single stream
- 163 tok/s on prose, 4 concurrent streams
- Prefill 5000 tok/s across the board.
3x DGX Sparks:
- 51 tok/s on prose, single stream
- 163 tok/s on prose, 4 concurrent streams
- Prefill 2000 tok/s across the board.
Also merged a lot of PRs and fixed a lot of issues.
Get it here:
mia-ai.net/models/DeepSeek-v…
Justin J Williams retweeted
DeepSeek V4.1 Flash 1017 Update: Using 44% Fewer Tokens, Running on Strix / Gorgon Halo with DwarfStar
youtu.be/A1vscZzkUg4
Justin J Williams retweeted
Coming to your 2xDGX Spark cluster soon!
DeepSeek v4.1 Flash 1017 FULLY UNCENSORED.
No cheap system prompts, no cheap template tricks, no lora or runtime bs, no sft. Model’s capabilities preserved as much as possible.
Complies with all requests on low/max reasoning efforts.
I’ll be making NVFP4 and a ~2.8bpw version for 2x DGX Sparks soon too.
huggingface.co/dealignai/Dee…
Justin J Williams retweeted
The potential impact of the ConnectWise supply chain attack is massive.
One compromised OAuth application with elevated permissions could give attackers access to emails, files, and directory data across hundreds of Microsoft 365 tenants.
Even worse, attackers could establish persistent access by adding credentials to other applications, surviving the revocation of the original compromised credentials.
And with MSPs involved, the potential blast radius could extend even further to downstream customers.
We don't know the full extent of the compromise yet, but this could affect far more organizations than those directly using ConnectWise Cloud Backup.
linkedin.com/posts/microsoft…
Justin J Williams retweeted
Exciting weekend! Was very happy to be racing our GT3 car in PortimĂŁo. There were some ups and downs, but as a team we learnt a lot.
I also feel I need to speak up about the hate and harassment Chris has received after the race. Everyone can have their opinions about what happened on track, but these personal attacks are not okay. Chris had a really strong stint and mistakes can happen.
There’s no place for this kind of abuse in our sport or anywhere else.
Justin J Williams retweeted
NEW DeepSeek v4.1 Flash-1017 is LIVE!! 🔥
Looks like it improved on everything!
Link below.
Justin J Williams retweeted
Another week, another proof point on autonomous AI attacks
CERT-In has published Advisory on its website:
AI Agents as Attack Vectors: Unauthorized Access by Agents under Evaluation and Misuse of Open-Source Agentic AI Tools Targeting Indian ICT Assets
cert-in.org.in/s2cMainServle…
Justin J Williams retweeted
This is interesting:
We're open sourcing SPACE, the sandbox platform that runs every task in Perplexity Computer.
SPACE gives each agent task its own Firecracker microVM and controls credentials and outbound traffic from outside the VM.
Available now under Apache 2.0: github.com/perplexityai/SPAC…
Justin J Williams retweeted
Replying to @Arikalabs
ddalcu.github.io/kkrieger/ made it playable on web.
Justin J Williams retweeted
• GLM-5.3 full, EXL3 3.38bpw, 4 DGX Sparks
• RED-SNOW 5.3 Flash, EXL3 4.91bpw, 2 Sparks
• RED-SNOW 5.3 Flash, EXL3 2.49bpw, 1 Spark
Steam train prompt:
-GLM full: 331K tokens, 2.9 hrs, ~32 tok/s
-RED-SNOW 4.91: 191K tokens, 1.3 hrs, ~44 tok/s
-RED-SNOW 2.49: 235K tokens, 2.1 hrs, ~30 tok/s
How the fixes work: after each try, the model gets a plain report of what its page did (errors, brightness, motion, what's on screen). No hints. It either keeps the page or fixes file. Max 3 rounds. All three used all 3.
No human edits. Thinking on.
4 Sparks gave the most detail. 2 Sparks got there for less than half the time.
Justin J Williams retweeted
Today we’re taking another step toward our vision of an agent for every person and every process.
Last month, we started rolling out Autopilot. Today, Copilot Studio is taking the next step with persistent agents in Microsoft 365. This means each agent can have its own account, so people can email it, add it to a Teams chat or channel or mention it in Word, Excel or PowerPoint. Business process memory carries all the teamwork and context forward in the next cycles all while IT stays in control.
The first capabilities begin rolling out in preview today, with more planned.
aka.ms/persistentagents/blog
Justin J Williams retweeted
Fresh @Mandiant and GTIG blog detailing zero day exploitation of CVE-2026-102764 in BeyondTrust Remote Support by 🇨🇳 nexus espionage actor ARMORY CASTLE (fka UNC5221).
cloud.google.com/blog/topics…
Justin J Williams retweeted
We have post-trained GLM 5.3 flash to become as strong as Fable 5.1 on SRE tasks (that is bug finding in complicated software deployments). Checkout our tech paper to see how we did it. web-assets.dd-static.net/425…
Justin J Williams retweeted
developer.nvidia.com/blog/nv…
Open source! This is huge news!
TensorFold's first community challenge runs from 14 to 21 October. đź‘€
Make your setup faster, use less memory or get a model working, then share what helped and help someone else.
There may or may not be a prize for the most voted.
We would love you to join us: discord.gg/5GUpUeWmS
Justin J Williams retweeted
[NEW RELEASE] Between March and October, the AI security field stopped asking how to roll AI out and started asking how to survive it. @IndreAltman and I serve on the @unpromptedconf AI Security Practitioner Conference team, and when we lined up March 2026’s 469 submissions against October 2026’s 490, the shift stunned us both.
A call for papers is a census nobody else gets to take. Roughly 500 submissions in each round, each is someone describing what they are actually working on before it's shaped by committee. Only a fraction are accepted, so the final program doesn't show what the whole field is chasing. The full pile does. (I have always been more curious about the pile than the program.)
The two [un]prompted CFP rounds bracket April when Glasswing and Mythos landed. The Mythos moment helped change the industry. We wanted to know whether it changed what researchers turned in. It did.
The pattern under October’s 490 has less to do with a technology than an industry anxiety.
348 submissions, 71%, touch agentic systems. The headline is not “everyone is doing agents.” It is "can we trust the agents we have already deployed," and whether we can tell you what an agent actually did after the fact.
94 submissions use the word “harness,” a term that barely existed in this field a year ago. The scaffolding around the model is the attack surface: the tools, the memory, the permissions, the execution loop wrapped around the model.
Proposals describing attacks on the harness layer rose from 12 in March to 33 in October, a 175% increase. Attackers go after that layer now, and defenders are still working out how to see into it. (We have a word for it before we have a way to secure it, which is the usual order of operations in this business.)
71% of October’s pool is agent-native: the harness, the MCP and skill supply chain, agent identity, prompt injection and its many children, agentic-browser attacks.
12% of submissions carry production evidence. The other 88% are experiment and prototype. The agents are in production and most of the research about them is not. (I keep going back and forth on whether that is people being careful or people being behind. Probably both.)
This is not the March field with a few new talks bolted on. It is a different room.
Those are a few of the findings. Indre and I wrote the rest up as the State of AI Cybersecurity report. Read it and see for yourself what changed. unpromptedcon.org
@unpromptedconf 27-29 Oct in SF. Almost sold out!
@unpromptedconf @SANSInstitute @gadievron @jaybeale @aaronzollman @jonsakoda @WHITEHACKSEC @dhubbard858 @brittaglade @GuanniQu @EmanuelGawrieh @GregNotch @joesu11ivan @dragosr @IdaVass1








































