Techbest – Top Tech Reviews In Australia
The best in Australian gadgets and technology
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SoundMAGIC T80BT ANC True Wireless Earbuds with Hi-Res Audio,Hibrid Active Noise Cancelling, ENC Call Clarity, 20H Playtime, IPX5 Waterproof, Ultra-Comfy Fit for Sports/Work/Gaming (Blue)
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QCY Crossky C50 Clip On Earbuds Open Ear Wireless Bluetooth 6.0 Headphones with 4 Mic, 35H Playtime Ear Cuff Earbuds Comfortable for Running/Fintness, IPX5 Waterproof, Ultra Lightweight
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Initially focused on only two vulnerabilities, RondoDox has greatly broadened its attack landscape, now compromising 56 vulnerabilities across more than 30 vendors. This expansion is defined by the “exploit shotgun” method, wherein multiple exploits are deployed simultaneously to identify successful points of compromise.
The botnet’s toolkit comprises an impressive selection of exploits, featuring 50 command injection vulnerabilities, two path traversal issues, as well as examples of buffer overflow, authentication bypass, and memory corruption. Significantly, RondoDox also takes advantage of legacy vulnerabilities, including the well-known Shellshock bug from a decade ago.
RondoDox utilizes advanced methods to ensure persistence and evade detection. It mimics authentic traffic from gaming services and VPNs, camouflaging its actions as regular network activity. The malware alters system startup files and creates crontab entries to ensure its continued operation on compromised devices.
Distributed via a loader-as-a-service (LaaS) framework, the botnet is bundled with other malicious payloads such as Mirai and Morte. This framework allows for extensive distribution, equipping attackers with a comprehensive botnet panel for managing malicious requests.
RondoDox’s attack methods encompass both consumer and enterprise devices, including Oracle WebLogic servers, WordPress, and vBulletin systems. The malware is designed to support various Linux architectures, enhancing its potential reach across multiple devices and platforms.
RondoDox signifies a notable advancement in IoT botnet operations, demonstrating its capacity to exploit a diverse array of vulnerabilities across many vendors. Its unique distribution strategies and advanced evasion techniques render it a significant threat to both personal and organizational networks.
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HUAWEI FreeBuds Pro 4, Wireless Earbuds, Real Sound with Dual Driver, Stable and Clear Calls, Dynamic Smart ANC, Compatible with iOS&Android, Noise Cancelling, White
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OPPO Enco X Wireless Bluetooth Earbuds – Black
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Skullcandy Indy Evo Wireless Earphones, Black
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Xiaomi Redmi Buds 6 Pro Active Noise Cancelling up to 55dB Advanced Triple Driver LDAC Compatible High Resolution Audio Wireless Up to 36 Hours Music Playback Google Fast Pair Space Black
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HUAWEI FreeClip, Rose Gold, Wireless Bluetooth Headphones, Innovative Aesthetic Design, Featherlight Use
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sajawass Wireless Earbuds, 75H Playtime Bluetooth 5.3 Headphones, IP7 Waterproof for Running, Wireless in-Ear Earphones for iOS/Android
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Google DeepMind’s newest creation, CodeMender, signifies a major leap in applying artificial intelligence to tackle software vulnerabilities. This AI agent is engineered to instantaneously detect and rectify security flaws, empowering developers in the relentless effort to secure codebases.
CodeMender employs the latest Gemini Deep Think models to facilitate self-sufficient debugging and resolution of intricate vulnerabilities. These models provide the AI with analytical tools to implement effective code modifications, which are subsequently validated automatically to avert regressions and new troubles.
Although CodeMender autonomously detects and proposes patches, these AI-created solutions undergo human scrutiny before they are enacted. This cooperative model guarantees that the patches not only remedy the problem but also conform to style standards, making them more comprehensible for human developers to review and endorse.
In the last six months, CodeMender has made 72 security contributions to open-source projects, managing codebases as large as 4.5 million lines. Remarkably, the tool has pinpointed and rectified complex problems like memory heap buffer overflows and improved the libwebp library by implementing bounds checks to avert buffer overflows.
Google intends to solicit feedback from open-source project maintainers to further hone CodeMender prior to its broader deployment. Additionally, DeepMind is gearing up to release comprehensive technical documents on the tool. The role of AI in security is expanding, evident from other DeepMind projects such as the Big Sleep tool and Google’s initiatives for AI-driven ransomware detection in the Workspace productivity suite.
Google DeepMind’s CodeMender serves as an AI-driven solution aimed at autonomously identifying and patching software vulnerabilities. By utilizing state-of-the-art AI models paired with a human review process, CodeMender has already made notable contributions to open-source initiatives, highlighting AI’s potential in bolstering software security.
