
Veteran-owned 501(c)(3) nonprofit delivering free cybersecurity education, training, and tools | Operating @usetraceix @SecureLegion and @VeilanceApp
Joined March 2025
- Tweets3.8K
- Following18
- Followers3.7K
- Likes1.5K
Pinned Tweet
I’ll pay you to browse the web.
More info in the quoted post👇
We will pay you to browse the internet.
How?
- Install Veilance: veilance.org
- Go through the onboarding process and enable automated telemetry
- Start browsing the web like you normally would
- Profit
It’s literally that simple.
I spent the last ~6 hours building a reliable (kinda) php exploit for the RCE that came out today. Specifically I built the OOM corruption exploit.
Here’s what I’ve learned from it:
- this is a very unreliable exploit. the corruption is easy to trigger but getting the correct address and everything back in real situations is not easy
- it appears to only work with apache, which is fine but narrows the attack surface a bit (im not 100% on this if its wrong lemme know)
- there has not been a massive uptick in exploits from this as everyone expected
- the reliability is EXTREMELY dependent on the build, and infrastructure
In other words, I hate this rce, and would never use it in a real world attack.
PCEF retweeted
Another major milestone for Veilance and the entire ecosystem.
After almost a month of development and training, we've finished six rounds of models, ranging from 4 billion to 32 billion parameters, with an infrastructure cost of $3,511.02 USD.
To accomplish this training, we leveraged infrastructure hosted on lambda.ai, equipped with:
- 56 vCPUs
- 400 GB of RAM
- 4 NVIDIA A6000 GPUs
Training at this scale requires massive amounts of computational power, and thanks to the @nvidia Inception program, we leveraged our access to GPU credits to cover the infrastructure cost.
This support provided us with access to the compute power needed to complete the Verity training and reach a major milestone that would have otherwise required massive amounts of out of pocket expenses we can now use for marketing, and fund raising.
The result? Verity: a large language model built to specialize around privacy on the web.
Unlike general use LLMs, Verity was developed to help users understand how websites collect, process, and share their information. Its capabilities include:
- Analyzing websites and their privacy policies.
- Providing advice and recommendations to improve online privacy.
- Explaining complex privacy information in language easy to understand.
- Accessing and analyzing intelligence collected through the Veilance Intelligence Network.
- Helping users understand relationships between what websites disclose in their policies and what their behavior actually reveals.
This is way more than just completing a training run. We've built specialized AI infrastructure around real browser telemetry and privacy intelligence, with the goal of making online privacy much more transparent, understandable, and accessible.
A huge thank you to @nvidia for access to the Inception program for their help in making this possible.
The completion of Verity is a massive step forward for Veilance, and we're ecstatic about what comes next.
Verity is ready for production. Verity-32B-v3 will be used as our production model and will be replacing our current OpenAI model once we have the infrastructure ready to support it the switch.
To celebrate we have released more than 10GB of training data across 4 different versions that we used to train Verity. You can find the datasets in the following links:
- Version 1: huggingface.co/datasets/Veil…
- Version 2: huggingface.co/datasets/Veil…
- Version 3: huggingface.co/datasets/Veil…
- Version 4: huggingface.co/datasets/Veil…
These datasets each make up a training set for the Verity AI and was used during the training of one of the models we have released.
PCEF retweeted
Introducing the Veilance Intelligence Network.
Search across thousands of real life website visits, and compare website behavior across multiple countries and real user sessions.
Learn more today: veilance.org/intel-network
Get paid to upload anonymized telemetry: veilance.org/paid-to-browse
The token to equity process is closed, we are no longer accepting new participants.
Those who were accepted are becoming shareholders of Revix Technologies, Inc.
I’m looking forward to working with each of you and building what comes next together.
PCEF retweeted
We had to shut off Traceix.
Our AI did something weird and started processing files on the host machine instead of files that were received via the upload pipeline.
It didn’t do anything nefarious, it just kind of started analyzing local files and we don’t know why.
PCEF retweeted
Verity-4B-RC has been trained and is working successfully.
It has approximately a ~72% task score up from ~50% from the last version.
The new version of Verity will be released later on. Afterwards, we’ll be opensourcing older Verity versions once they are no longer in use.
It is our pleasure to host this for you and get more eyes on privacy related content
You’re unable to view this Post because this account owner limits who can view their Posts. Learn more
Pre-allocation KYC is available. We may require you to provide more documentation. You will have 1 week to fill this out: forms.gle/SkzDra4fC3hTEbT3A
The link will no longer be accessible next Friday Sept 18th, 2026
Revix Technologies has been accepted into the Nvidia Inception program.
Yesterday, we were accepted into the @NVIDIA Inception program.
Through our participation in the program, we gain access to a wide range of benefits: GPU credits, discounts, training resources, and access to a large investor and VC network.
This is a massive win and milestone.
Revix Technologies Inc. is now part of the Intel Partner Alliance program!
We’re excited to announce that we’ve been accepted into @Intel’s Partner Alliance program!
We’re currently finalizing our storefront and expect it to be live within the next ~96 hours, where we’ll be featured in Intel’s partner showcase!
You all thought I was playing. I assure I was not, meet: malwaregooning.com/
Opensource as well, find it here: github.com/Perkins-Fund/Malw…
The current files are just examples.












