Building Pentest Copilot: autonomous pentesting with AI agents. Enterprise pentesting and bug bounty programs.
Joined May 2021
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4/ Pentest Copilot tests real attack paths, validates exploitability, and retests fixes to confirm they hold. Stratus brings the FedRAMP depth to turn that into VDR/VER reporting.
Working through VDR/VER before Dec 7? Let's talk: copilot.bugbase.ai
3/ Scanners produce CVE lists, and FedRAMP itself says most aren't likely exploitable. An annual pentest is a snapshot.
Neither tells you week to week which findings are real, or whether a fix held.
2/ The new rules change what a provider has to know about every vuln:
Is it likely exploitable?
Is it internet-reachable, even indirectly?
What's the impact on agencies?
Those answers set the fix clock. For the worst cases, that's days.
BugBase retweeted
We built Caido to be API-first. Now an open source AI pentest agent drives Caido.
Pentest Copilot, from @BugBase, added Caido as a first-class backend: HTTP History, Replay, Automate, Intercept, and OAST.
It all runs on our official SDK, and works over MCP too.
This is what API-first is for.
Try it now github.com/bugbasesecurity/p…
Pentest Copilot OSS now supports Caido.
Our goal with Pentest Copilot is simple: bring agentic pentesting capabilities to every pentester and bug bounty hunter.
We've added support for Caido across HTTP History, Replay, Automate, Intercept, and OAST.
🔗 github.com/bugbasesecurity/p…
Pentest Copilot OSS now supports Caido.
Our goal with Pentest Copilot is simple: bring agentic pentesting capabilities to every pentester and bug bounty hunter.
We've added support for Caido across HTTP History, Replay, Automate, Intercept, and OAST.
🔗 github.com/bugbasesecurity/p…
Join us for Live hacking event with @_groww
What’s in it for you?
- Bounty rewards up to $7,500 per eligible bug (severity‑based)
- Special prizes for the Most Valuable Hacker & the Top 3 performers
- When: April 25/26, 2025
- Where: Bangalore
- RSVP: forms.gle/o9safenDh9f3khQB7
BugBase retweeted
Pentest Copilot by @BugBase demonstrates lateral movement in network using an SSH key found on a compromised host. The video shows the complete attack flow from the compromised host to running the agent(RAT) on the remote host with a clear, step-by-step exploit graph.
Special campaign alert: Groww’s Bug Bounty now offers 1.5x rewards for vulnerabilities risking PII exposure & security control bypass.
Join here: bugbase.ai/programs/groww
#Groww #BugBounty #CyberSecurity #Infosec
@_groww
Wishing everyone a very Happy New Year 2025! 🎉
We ended 2024 with our first live hacking event in collaboration with @ClearfromCT and @Nullblr.
In 2025, we’re aiming even higher with larger events, bigger collaborations, and more opportunities for researchers.
💥 Groww just launched a Bug Bounty program on BugBase with rewards of up to $3,000! 🚀 Are you ready to hunt vulnerabilities & secure the future of finance? 💰🔍
👉 Start now: bugbase.ai/programs/groww
#BugBounty #CyberSecurity #Groww #BugBase #EarnRewards
Missed the Webinar on "Comprehensive Analysis of JWT Vulnerabilities" by Pragya Gupta, Security Engineer at PhonePe?
Watch the Full Recording Now: youtu.be/xgl0uEbPO-M
#BugBase #Webinar #BugGyaan #JWTs #Cybersecurity
Deep Learning Specialization by Andrew Ng: deeplearning.ai/courses/deep…
Neural Networks by 3Blue1Brown: 3blue1brown.com/topics/neura…
A gentle introduction to Machine Learning by StatQuest with Josh Starmer: youtube.com/playlist?list=PL…
#Cybersecurity #AI #MachineLearning #LearningResources
These topics act as a good starting point for anyone willing to get a basic intuitive understanding of AI.
For further learning, check out these resources:
🧠 Deep Learning Basics:
- Neural Networks: Explore the basics of neural networks, the building blocks of deep learning.
- Convolutional Neural Networks (CNNs): Discover how CNNs are used for image recognition and general classification.
🕸️ Advanced Machine Learning Techniques:
- Decision Trees: Understand how decision trees can be used for classification and regression tasks.
- Graphs: Explore the use of graph-based models in machine learning.