{"id":138938,"date":"2025-07-14T11:11:58","date_gmt":"2025-07-14T09:11:59","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/gpuhammer-variant-ataki-rowhammer-na-pamyat-gpu"},"modified":"2025-07-14T11:11:58","modified_gmt":"2025-07-14T09:11:59","slug":"gpuhammer-variant-ataki-rowhammer-na-pamyat-gpu","status":"publish","type":"post","link":"https:\/\/prohoster.info\/no\/blog\/news\/gpuhammer-variant-ataki-rowhammer-na-pamyat-gpu","title":{"rendered":"GPUHammer \u2014 en variant av Rowhammer-angrepet p\u00e5 GPU-minne","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Forskere fra Universitetet i Toronto har presentert den f\u00f8rste Rowhammer-angrepsklassen som brukes til \u00e5 fordreie innholdet i videominne. Muligheten for et angrep som kan for\u00e5rsake substitusjon av opptil 8 biter med data, ble demonstrert p\u00e5 det diskrete GPU NVIDIA A6000 med GDDR6 videominne. Som et praktisk eksempel ble det vist hvordan en slik fordreining kan brukes til \u00e5 p\u00e5virke utf\u00f8relsen av maskinl\u00e6ringsmodeller, med en betydelig reduksjon i n\u00f8yaktigheten av resultatene de gir (fra 80 % til 0.1 %) ved \u00e5 endre verdien av bare \u00e9n bit.

\"GPUHammer<\/center> <\/p>\n

Frem til n\u00e5 har det v\u00e6rt vanskelig \u00e5 skape Rowhammer-angrep mot videominne p\u00e5 grunn av kompleksiteten med \u00e5 bestemme den fysiske layouten av minnet i GDDR-brikker, samt de store forsinkelsene ved tilgang til minnet (fire ganger tregere) og h\u00f8yere oppdateringsfrekvens av minnet. I tillegg har bruken av propriet\u00e6re beskyttelsesmekanismer mot manipulasjoner, som f\u00f8rer til tidlig tap av lading, i GDDR-brikker vanskeliggjort forskningen, noe som har krevd oppsett av spesielle maskinvare teststasjoner basert p\u00e5 FPGA. <\/p>\n

For \u00e5 studere videominne har forskerne utviklet en ny teknikk for reversering av GDDR DRAM, og i angrepet ble det benyttet optimeringer for minnetilgang som brukes for parallell beregning, og disse ble brukt som intensitetsforsterkere for tilgang til individuelle celler. For \u00e5 utf\u00f8re angrepet p\u00e5 NVIDIA GPU ble det brukt lavniv\u00e5 CUDA-kode. <\/p>\n

I brukerens CUDA-kode gj\u00f8res det ikke henvisning til fysiske minneadresser, men i NVIDIA-driveren ble den virtuelle hukommelsen reflektert i samme fysiske minne, som forskerne utnyttet for \u00e5 beregne offset for virtuell hukommelse og bestemme banklayouten for minnet. Gjenkjennelsen av henvisninger til forskjellige minnebiler ble gjort ved \u00e5 analysere forsinkelsene, som var forskjellige ved tilgang til \u00e9n eller flere minnebiler. <\/p>\n

I systemer som deler GPU, som servere<\/a> For executing machine learning models, the attack allows one user to alter the contents of another user\u2019s video memory. As a protective measure, NVIDIA recommends enabling Error Correction Codes (ECC) using the command «nvidia-smi -e 1» or utilizing graphics card series that support OD-ECC (On-Die ECC), such as GeForce RTX 50, RTX PRO, GB200, B200, B100, H100, H200, H20, and GH200. <\/p>\n

According to researchers, enabling ECC on systems with GPU A6000 leads to a decrease in the performance of machine learning models by about 10% and a reduction in memory volume by 6.25%. The toolkit for carrying out the attack and performing low-level reverse engineering of video memory layout on systems with NVIDIA GPU has been published on GitHub. <\/p>\n

RowHammer-angrepet lar deg forvrenge innholdet i individuelle DRAM-minnebiter ved \u00e5 utf\u00f8re kontinuerlig lesing av data fra naboceller. Siden DRAM-minnet er en todimensjonal matrise av celler, der hver celle best\u00e5r av en kondensator og en transistor, f\u00f8rer kontinuerlig lesing av samme minneomr\u00e5de til spenningsfluktuasjoner og anomalier som for\u00e5rsaker et lite ladetap i naboceller. Hvis leseintensiteten er h\u00f8y, kan en nabocelle miste tilstrekkelig mengde ladning, og den p\u00e5f\u00f8lgende regenereringssyklusen kan ikke gjenopprette dens opprinnelige tilstand, noe som resulterer i at verdiene lagret i cellen endres. <\/p>\n

The Rowhammer attack method was proposed in 2014, after which a 'cat-and-mouse' game began between security researchers and hardware manufacturers \u2014 chip makers attempted to block the vulnerability, while researchers found new ways to bypass it. For example, to protect against Rowhammer, chip manufacturers added the TRR (Target Row Refresh) mechanism, but it turned out that it only mitigates cell distortion in specific cases, failing to protect against all potential attack vectors. Attack methods have been developed for DDR3, DDR4, and DDR5 chips on systems with Intel, AMD, and ARM processors. Ways to circumvent ECC corrections were also discovered, along with options for conducting attacks over networks and through executing JavaScript code in browsers.
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Kilde: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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