Presenting rFactor, the racing simulation series from Image Space Incorporated and now Studio 397. After successfully creating over a dozen products in the previous ten years, including the Formula One and NASCAR franchise games for EA Sports, Image Space took the next logical step in creating a completely new technology base and development process. This new isiMotor 2.0 environment became the foundation on which many exciting products were built for years to come.
The newest creation, rFactor 2, creates a dynamic racing environment that for the first time put you the driver into a racing simulator, instead of just a physics simulator. Changing tires, track surfaces, grip, weather and lighting make rFactor 2 a true challenge to any sim racer.
If you're looking for up-to-date visuals, advanced physics, first-party Studio 397-produced content, and licensed vehicles from major manufacturers and racing series, then rFactor 2 is for you. Want access to a massive amount of third-party mods including dirt racing and drag racing, all working on the open rFactor modding platform? rFactor is what you should be looking at.
Both rFactor and rFactor 2 can be found on Steam (an online digital download games library).
The 2017 Formula E Visa Vegas eRace had a $1,000,000 prize pool, and used rFactor 2 as their simulator. The event and $200,000 1st-place prize was won by Bono Huis, a five time rFactor Formula Sim Racing Champion.
McLaren's World's Fastest Gamer contest promised a role with the Formula 1 team as one of its official simulator drivers, and they used rFactor 2 for their opening and final rounds. The event and role at McLaren was won by Rudy van Buren, a qualifier from the rFactor 2 opening round.
While sim racing eSports are still an emerging field, it's obvious from the results so far that the rFactor 2 simulation platform gives the flexibility in content and features required. This is the simulator you need to take part in events like those above, or upcoming events organized by Studio 397 in a competitive competition structure now in-development.
Given the context of Alarum Technologies (formerly known as Safe-T), this feature focuses on their , which align with the acronym "TCR" (Threat Compression Rate) or a proprietary script-based filtering system. Alarum TCRIP: Redefining Network Micro-Segmentation and Threat Compression In the modern zero-trust landscape, exposing entire network infrastructures to third parties is a liability. Alarum Technologies (TASE: ALAR) has pioneered a solution often referred to under its internal codename "TCRIP"—a sophisticated Threat Compression & Reverse Inspection Protocol .
return "FORWARD to origin" Alarum’s TCRIP script represents a paradigm shift from "perimeter defense" to query-level zero trust . By compressing threat intelligence into real-time inspection rules, organizations can protect their most sensitive databases without sacrificing performance. alarum tcrip
TCRIP is available as part of Alarum’s Access Management Suite. Contact Alarum Technologies for a proof-of-concept deployment on your PostgreSQL, MySQL, or MongoDB clusters. Note: If "TCRIP" refers to a specific product name or internal tool not yet publicly documented, this feature extrapolates from Alarum’s published patents on Threat Compression and Reverse Access Proxies. Always refer to the official Alarum documentation for exact specifications. Given the context of Alarum Technologies (formerly known
# Step 3: Enforce data exfiltration limits if estimated_response_size(request_payload) > user_context.max_rows: return "TRUNCATE - Limit exceeded" At its core
Here is how this technology transforms enterprise security. TCRIP is not a standard firewall or VPN. It is a proprietary application-layer filtering script that operates on Alarum’s NetNut and Secure-T platforms. At its core, TCRIP executes a "threat compression" algorithm: instead of inspecting every packet (which is slow), it compresses malicious behavioral signatures into a lightweight real-time inspection profile.
# Alarum TCRIP - Inspection Hook def tcr_inspect(request_payload, user_context): # Step 1: Compress threat signature compressed_sig = threat_compressor(request_payload) # Step 2: Match against known attack patterns if compressed_sig in BLOCKLIST_SIGNATURES: log_anomaly("TCRIP_BLOCK", user_context) return "REJECT - Threat compressed"
