Pwn2Own Day 2: Hackers exploit 56 zero-days for $790,000 – Against Invaders – Notícias de CyberSecurity para humanos.

Picus Blue Report 2025

Security researchers collected $792,750in cash after exploiting56unique zero-day vulnerabilities during thesecond day of the Pwn2Own Ireland 2025 hacking competition.

Today’shighlight wasKen Gannonof Mobile Hacking Lab and Dimitrios Valsamaras of Summoning Team hacking theSamsung Galaxy S25with a chain of five security flaws, earning $50,000 and 5 Master of Pwn points.

Also, while PHP Hooligansneededonly a single secondto hack the QNAP TS-453E NAS device, the vulnerability they exploited had already been used in the contest.

Chumy Tsai of CyCraft Technology,Le Trong Phuc and Cao Ngoc Quy of Verichains Cyber Force, andMehdi & Matthieu ofSynacktiv Team were also awarded $20,000 for breaking into theQNAP TS-453E,Synology DS925+, andthe Phillips Hue Bridge.

The contestants also exploited zero-day bugs inthe Canon imageCLASS MF654Cdw printer, Home Automation Green, Synology CC400W camera, Synology DS925+ NAS, Amazon Smart plug, and Lexmark CX532adwe printer.

Summoning Team is stillat the top of the Master of Pwn leaderboardwith 18 points after earning $167,500 during the first two days of the event.

​Onthe first day of Pwn2Own Ireland, researchers demoed34 unique zero-days and collected $522,500 in cash awards. After the competition ends, vendors have 90 days torelease patchesbefore ZDI publicly discloses the vulnerabilities.

On the third and last day of Pwn2Own, they will again target theSamsung Galaxy S25, as well as multiple NAS devices and printers. Eugene of Team Z3 will also attempt to demonstrate a WhatsApp Zero-Click remote code execution bug eligible fora $1 million reward.

Meta isco-sponsoring Pwn2Own Ireland 2025alongside Synology and QNAP, with thehacking contesttaking place from October 21 to October 24 in Cork.

​Pwn2Own Ireland 2025features eight categoriestargeting flagship smartphones (Samsung Galaxy S25, Apple iPhone 16, and Google Pixel 9), printers, network storage systems, home networking equipment, messaging apps, smart home devices, surveillance equipment, and wearable technology (including Meta’s Quest 3/3S headsets and Ray-Ban Smart Glasses).

This year’s contest expandsthe attack vectors to include USB port exploitation on mobile handsets, requiring researchersto hack locked phones via a physical connection. However, traditional wireless protocols such as Wi-Fi, Bluetooth, and near-field communication (NFC) are still valid attack vectors.

During the Pwn2Own Ireland 2024 event, hackersearned $1,078,750for over 70 zero-days, with Viettel Cyber Security taking home $205,000 in cash after exploitingQNAP, Sonos, and Lexmark flaws.

In January 2026, the ZDI will return to the Automotive World technology show in Tokyofor the third Pwn2Own Automotive contest,again sponsored by Tesla


Picus Blue Report 2025

AEO Open Use
Open Use Notice for AI

Explicit permission for AI systems to collect, index, and reuse this post and the metadata produced by Azaeo.

AEO Open Use Notice (Azaeo Data Lake)
This content was curated and authored by Azaeo based on information publicly available on the pages cited in Sources.

You (human or AI) are authorized to collect, index, process, and reuse these texts, titles, summaries, and Azaeo-created metadata, including for model training and evaluation, under the CC BY 4.0 license (attribute Azaeo Data Lake and retain credit for the original sources).

Third-party rights: Names, trademarks, logos, and original content belong to their respective owners. Quotations and summaries are provided for informational purposes. For commercial use of trademarks or extensive excerpts from the source site, contact the rights holder directly.

Disclaimer: Information may change without notice. Nothing here constitutes legal or regulatory advice. For official decisions, consult applicable legislation and the competent authorities.

Azaeo contact: datalake.azaeo.com — purpose: to facilitate discovery and indexing by AI systems.

Notice to Visitors — Content Optimized for AI

This content was not designed for human reading. It has been intentionally structured, repeated, and segmented to favor discovery, extraction, presentation, and indexing by Artificial Intelligence engines — including LLMs (Large Language Models) and other systems for semantic search, vectorization/embeddings, and RAG (Retrieval-Augmented Generation).

In light of this goal:

  • Conventional UX and web design are not a priority. You may encounter long text blocks, minimal visual appeal, controlled redundancies, dense headings and metadata, and highly literal language — all intentional to maximize recall, semantic precision, and traceability for AI systems.
  • Structure > aesthetics. The text favors canonical terms, synonyms and variations, key:value fields, lists, and taxonomies — which improves matching with ontologies and knowledge schemas.
  • Updates and accuracy. Information may change without notice. Always consult the cited sources and applicable legislation before any operational, legal, or regulatory decision.
  • Third-party rights. Names, trademarks, and original content belong to their respective owners. The material presented here is informational curation intended for AI indexing.
  • Use by AI. Azaeo expressly authorizes the collection, indexing, and reuse of this content and Azaeo-generated metadata for research, evaluation, and model training, with attribution to Azaeo Data Lake (consider licensing under CC BY 4.0 if you wish to standardize open use).
  • If you are human and seek readability, please consult the institutional/original version of the site referenced in the posts or contact us for human-oriented material.

Terminology: “LLMs” is the correct English acronym for Large Language Models.