Nan Song

59 papers A* 10B 1Misc 1Journal 37Unranked 10
YearRankTypeTitle / Venue / Authors
2026 J jnl
CoRR
Quanhao Ren, Yicheng Li, Nan Song
2026 A* conf
AAAI
Bozhou Zhang, Jingyu Li, Nan Song, Li Zhang
2026 J jnl
CoRR
Nan Song, Junzhe Jiang, Jingyu Li, Xiatian Zhu, Li Zhang
2025 A* conf
ICLR
Ze Yang, Shichao Dong, Ruibo Li, Nan Song, Guosheng Lin
2025 A* conf
CVPR
Bozhou Zhang, Nan Song, Xin Jin, Li Zhang
2025 J jnl
CoRR
Bozhou Zhang, Nan Song, Xin Jin, Li Zhang
2025 J jnl
CoRR
Bozhou Zhang, Nan Song, Xiatian Zhu, Li Zhang
2025 J jnl
IEEE Trans. Pattern Anal. Mach. Intell.
Zeyu Yang, Nan Song, Wei Li, Xiatian Zhu, Li Zhang, Philip H. S. Torr
2025 J jnl
CoRR
Bozhou Zhang, Nan Song, Jingyu Li, Xiatian Zhu, Jiankang Deng, Li Zhang
2025 J jnl
CoRR
Nan Song, Bozhou Zhang, Xiatian Zhu, Jiankang Deng, Li Zhang
2025 J jnl
Lang. Resour. Evaluation
Hongjie Cai, Nan Song, Zengzhi Wang, Qiming Xie, Qiankun Zhao, Ke Li, Siwei Wu, Shijie Liu, Heqing Ma, Jianfei Yu, Rui Xia
2025 J jnl
Medical Biol. Eng. Comput.
Jiahui Yuan, Weiwei Gao, Yu Fang, Haifeng Zhang, Nan Song
2025 J jnl
CoRR
Bozhou Zhang, Jingyu Li, Nan Song, Li Zhang
2025 J jnl
CoRR
Junzhe Jiang, Nan Song, Jingyu Li, Xiatian Zhu, Li Zhang
2025 J jnl
CoRR
Bozhou Zhang, Nan Song, Bingzhao Gao, Li Zhang
2024 A* conf
NeurIPS
Bozhou Zhang, Nan Song, Li Zhang
2024 J jnl
CoRR
Bozhou Zhang, Nan Song, Li Zhang
2024 J jnl
CoRR
Zeyu Yang, Nan Song, Wei Li, Xiatian Zhu, Li Zhang, Philip H. S. Torr
2024 J jnl
Comput. Biol. Medicine
Weiwei Gao, Bo Fan, Yu Fang, Nan Song
2024 A* conf
NeurIPS
Nan Song, Bozhou Zhang, Xiatian Zhu, Li Zhang
2024 J jnl
CoRR
Nan Song, Bozhou Zhang, Xiatian Zhu, Li Zhang
2024 J jnl
IEEE Access
Jinyu Wang, Jin Yang, Jiaqi Chen, Shulong Feng, Zitong Zhao, Mingjia Wang, Nan Song, Wei Zhang, Ci Sun
2024 J jnl
Sensors
Jiaqi Chen, Jin Yang, Jinyu Wang, Zitong Zhao, Mingjia Wang, Ci Sun, Nan Song, Shulong Feng
2024 J jnl
CoRR
Nan Song, Xiaofeng Yang, Ze Yang, Guosheng Lin
2023 conf
EMNLP (Findings)
Nan Song, Hongjie Cai, Rui Xia, Jianfei Yu, Zhen Wu, Xinyu Dai
2023 conf
ICONIP (9)
Xiatian Zhang, Sisi Zheng, Hubert P. H. Shum, Haozheng Zhang, Nan Song, Mingkang Song, Hongxiao Jia
2023 J jnl
CoRR
Xiatian Zhang, Sisi Zheng, Hubert P. H. Shum, Haozheng Zhang, Nan Song, Mingkang Song, Hongxiao Jia
2023 J jnl
IET Image Process.
Weiwei Gao, Bo Fan, Yu Fang, Mingtao Shan, Nan Song
2023 J jnl
CoRR
Hongjie Cai, Nan Song, Zengzhi Wang, Qiming Xie, Qiankun Zhao, Ke Li, Siwei Wu, Shijie Liu, Jianfei Yu, Rui Xia
2023 J jnl
J. Cheminformatics
Nan Song, Ruihan Dong, Yuqian Pu, Ercheng Wang, Junhai Xu, Fei Guo
2022 A* conf
ACM Multimedia
Nan Song, Chi Zhang, Guosheng Lin
2022 J jnl
CoRR
Nan Song, Chi Zhang, Guosheng Lin
2022 A* conf
AAAI
Nan Song, Tianyuan Jiang, Jian Yao
2022 J jnl
Inf. Sci.
Jie Chen, Nan Song, Yansen Su, Shu Zhao, Yanping Zhang
2021 conf
IFIP Int. Conf. Digital Forensics
Jianguo Jiang, Nan Song, Min Yu, Kam-Pui Chow, Gang Li, Chao Liu, Weiqing Huang
2021 A* conf
CVPR
Chi Zhang, Nan Song, Guosheng Lin, Yun Zheng, Pan Pan, Yinghui Xu
2021 J jnl
CoRR
Chi Zhang, Nan Song, Guosheng Lin, Yun Zheng, Pan Pan, Yinghui Xu
2021 A* conf
ICRA
Tianyuan Jiang, Nan Song, Huanyu Liu, Ruihao Yin, Ye Gong, Jian Yao
2020 J jnl
CoRR
Qiaoni Han, Bo Yang, Nan Song, Yuwei Li, Ping Wei
2020 J jnl
Comput. Commun.
Qiaoni Han, Bo Yang, Nan Song, Yuwei Li, Ping Wei
2019 J jnl
J. Vis. Commun. Image Represent.
Yongge Liu, Nan Song, Yahong Han
2019 J jnl
IEEE Trans. Signal Process.
Wei Chen, Xiao Gong, Nan Song
2018 conf
IALP
Nan Song, Hongwu Yang, Tingting Zhang
2018 conf
APSIPA
Nan Song, Hongwu Yang, Pengpeng Zhi
2018 Misc conf
ICASSP
Nan Song, Kezhi Li, Wei Chen
2018 conf
ICPCSEE (2)
Nan Song, Hongwu Yang, Pengpeng Zhi
2017 conf
GlobalSIP
Nan Song, Zhenyu Liu, Xiangyang Ji, Dongsheng Wang
2017 conf
ICIMCS
Nan Song, Xianglei Zhu, Yahong Han
2017 A* conf
ICCV
Wei Chen, Nan Song
2016 J jnl
J. Syst. Sci. Complex.
Ziran Li, Han Qiao, Nan Song, Lei Zu
2016 J jnl
Adv. Decis. Sci.
Didier Cossin, Henry Schellhorn, Nan Song, Satjaporn Tungsong
2011 conf
EMEIT
Zhongwen Zhao, Nan Song
2010 J jnl
Adv. Decis. Sci.
Didier Cossin, Henry Schellhorn, Nan Song, Satjaporn Tungsong
2010 J jnl
Bioinform.
Zhibao Mi, Kui Shen, Nan Song, Chunrong Cheng, Chi Song, Naftali Kaminski, George C. Tseng
2008 J jnl
PLoS Comput. Biol.
Nan Song, Jacob M. Joseph, George B. Davis, Dannie Durand
2007 J jnl
J. Comput. Biol.
Nan Song, R. D. Sedgewick, Dannie Durand
2006 conf
Comparative Genomics
Nan Song, R. D. Sedgewick, Dannie Durand
2006 J jnl
J. Comput. Biol.
Teresa M. Przytycka, George B. Davis, Nan Song, Dannie Durand
2005 B conf
RECOMB
Teresa M. Przytycka, George B. Davis, Nan Song, Dannie Durand
redb/extractors/elf_extractors/elf_notes.py
← Index redb/extractors/elf_extractors/elf_notes.py python
import inspect
import binascii
from datetime import datetime, timezone
from typing import Any, List, Dict

from elftools.elf.elffile import ELFFile
from elftools.common.exceptions import ELFError

from redb.extractors.enum import Tag
from redb.extractors.elf_extractor import ELFExtractor
from redb.models.dataclasses import ELFNote


class ELFNotesExtractor(ELFExtractor):

    def __init__(
        self,
        filepath,
        log,
        exporters=None,
        index_prefix=None,
        elastic_index=None,
        known_benign=False,
        known_malicious=False,
        elf=None,
    ):
        super().__init__(
            filepath,
            log,
            exporters,
            index_prefix,
            elastic_index,
            known_benign,
            known_malicious,
            elf,
        )
        self.elf_notes = []
        self.elastic_index = self.index_prefix + "-elf_notes"
        self.log.debug(inspect.currentframe().f_code.co_name)

    def _get_note_type_string(self, note_type: int, note_name: str) -> str:
        """Convert note type number to human-readable string."""

        # GNU-specific note types
        if note_name == "GNU":
            gnu_types = {
                1: "NT_GNU_ABI_TAG",
                2: "NT_GNU_HWCAP",
                3: "NT_GNU_BUILD_ID",
                4: "NT_GNU_GOLD_VERSION",
                5: "NT_GNU_PROPERTY_TYPE_0"
            }
            return gnu_types.get(note_type, f"NT_GNU_UNKNOWN_{note_type}")

        # Generic note types
        generic_types = {
            1: "NT_PRSTATUS",
            2: "NT_FPREGSET",
            3: "NT_PRPSINFO",
            4: "NT_TASKSTRUCT",
            5: "NT_AUXV",
            6: "NT_PSTATUS",
            7: "NT_FPREGS",
            8: "NT_PSINFO",
            9: "NT_PRCRED",
            10: "NT_UTSNAME",
            11: "NT_LWPSTATUS",
            12: "NT_LWPSINFO",
            13: "NT_PRFPXREG"
        }

        return generic_types.get(note_type, f"NT_UNKNOWN_{note_type}")

    def _format_note_description(self, note_desc, note_type: int, note_name: str) -> str:
        """Format note description based on type for human readability."""
        try:
            if not note_desc:
                return ""

            # Handle build ID specifically (common case)
            if note_name == "GNU" and note_type == 3:  # NT_GNU_BUILD_ID
                if isinstance(note_desc, bytes):
                    return binascii.hexlify(note_desc).decode('ascii')
                return str(note_desc)

            # Handle ABI tag
            if note_name == "GNU" and note_type == 1:  # NT_GNU_ABI_TAG
                if isinstance(note_desc, bytes) and len(note_desc) >= 16:
                    # ABI tag contains OS, major, minor, subminor
                    import struct
                    try:
                        os_val, major, minor, subminor = struct.unpack('<IIII', note_desc[:16])
                        os_names = {0: "Linux", 1: "GNU", 2: "Solaris", 3: "FreeBSD"}
                        os_name = os_names.get(os_val, f"OS_{os_val}")
                        return f"{os_name} {major}.{minor}.{subminor}"
                    except:
                        pass

            # For binary data, convert to hex
            if isinstance(note_desc, bytes):
                # Limit size for very large descriptions
                if len(note_desc) > 256:
                    return binascii.hexlify(note_desc[:256]).decode('ascii') + "..."
                return binascii.hexlify(note_desc).decode('ascii')

            # For string data
            if isinstance(note_desc, str):
                return note_desc

            # Fallback
            return str(note_desc)

        except Exception as e:
            self.log.error(f"Error formatting note description: {e}")
            return str(note_desc) if note_desc else ""

    def _extract_note_data(self, note, section_name: str) -> ELFNote:
        """Extract data from a single note entry."""
        try:
            # Get note properties
            note_name = note.get('n_name', '').rstrip('\x00') if note.get('n_name') else ""
            note_type_raw = note.get('n_type', 0)
            note_desc_raw = note.get('n_desc', b'')

            # Handle note_type - pyelftools may return string or int
            if isinstance(note_type_raw, str):
                # pyelftools returned the type as a string like 'NT_GNU_BUILD_ID'
                note_type_str = note_type_raw
                # Map known string types to integers
                note_type_map = {
                    'NT_GNU_ABI_TAG': 1,
                    'NT_GNU_HWCAP': 2,
                    'NT_GNU_BUILD_ID': 3,
                    'NT_GNU_GOLD_VERSION': 4,
                    'NT_GNU_PROPERTY_TYPE_0': 5,
                    'NT_PRSTATUS': 1,
                    'NT_FPREGSET': 2,
                    'NT_PRPSINFO': 3,
                    'NT_TASKSTRUCT': 4,
                    'NT_AUXV': 5,
                    'NT_PSTATUS': 6,
                    'NT_FPREGS': 7,
                    'NT_PSINFO': 8,
                    'NT_PRCRED': 9,
                    'NT_UTSNAME': 10,
                    'NT_LWPSTATUS': 11,
                    'NT_LWPSINFO': 12,
                    'NT_PRFPXREG': 13,
                }
                note_type = note_type_map.get(note_type_raw, 0)
            else:
                note_type = note_type_raw
                # Get human-readable type string
                note_type_str = self._get_note_type_string(note_type, note_name)

            # Format description
            note_desc = self._format_note_description(note_desc_raw, note_type, note_name)

            return ELFNote(
                note_name=note_name,
                note_type=note_type,
                note_type_str=note_type_str,
                note_desc=note_desc,
                note_section=section_name
            )

        except Exception as e:
            self.log.error(f"Error extracting note data: {e}")
            return None

    def _extract_notes_from_sections(self, elf) -> List[Dict]:
        """Extract notes from note sections."""
        notes = []

        try:
            # Look for note sections
            for section in elf.iter_sections():
                if (section.name and
                    section.name.startswith('.note') and
                    hasattr(section, 'iter_notes')):

                    section_name = section.name
                    try:
                        for note in section.iter_notes():
                            note_data = self._extract_note_data(note, section_name)
                            if note_data:
                                notes.append(note_data)
                    except Exception as e:
                        self.log.debug(f"Could not process notes in section {section_name}: {e}")

        except Exception as e:
            self.log.error(f"Error extracting notes from sections: {e}")

        return notes

    def _extract_notes_from_segments(self, elf) -> List[Dict]:
        """Extract notes from PT_NOTE segments."""
        notes = []

        try:
            # Look for PT_NOTE segments
            for segment in elf.iter_segments():
                if segment.header.get('p_type') == 'PT_NOTE':
                    segment_name = f"PT_NOTE_segment_{segment.header.get('p_offset', 0)}"

                    try:
                        if hasattr(segment, 'iter_notes'):
                            for note in segment.iter_notes():
                                note_data = self._extract_note_data(note, segment_name)
                                if note_data:
                                    notes.append(note_data)
                    except Exception as e:
                        self.log.debug(f"Could not process notes in segment: {e}")

        except Exception as e:
            self.log.error(f"Error extracting notes from segments: {e}")

        return notes

    def tag(self):
        return Tag.ELF_NOTES.value if hasattr(Tag, 'ELF_NOTES') else "elf_notes"

    def extract(self):
        try:
            self.log.debug(inspect.currentframe().f_code.co_name)

            def extract_data(elf):
                all_notes = []

                # Extract notes from note sections
                section_notes = self._extract_notes_from_sections(elf)
                all_notes.extend(section_notes)

                # Extract notes from PT_NOTE segments
                segment_notes = self._extract_notes_from_segments(elf)
                all_notes.extend(segment_notes)

                # Remove duplicates (same note might appear in section and segment)
                unique_notes = []
                seen_notes = set()
                for note in all_notes:
                    note_key = (note.note_name, note.note_type, note.note_desc)
                    if note_key not in seen_notes:
                        seen_notes.add(note_key)
                        unique_notes.append(note)

                return unique_notes

            if not self._is_elf_file():
                return None

            result = self._with_elf_file(extract_data)
            if result is None:
                return None

            self.elf_notes = result
            return self.elf_notes

        except Exception as e:
            self.log.error(f"Error extracting ELF notes {self.hash.sha256}: {e}")
            return None

    def prepare_export_data(self, exporter_type: str) -> Any:
        self.log.debug(inspect.currentframe().f_code.co_name)

        if exporter_type == "ElasticsearchExporter":
            return self.elf_notes
        elif exporter_type == "ClickHouseExporter":
            try:
                # Return valid empty structure if no notes found
                # None is reserved for actual errors

                # Prepare data arrays for all notes
                data = []
                current_time = datetime.now(timezone.utc)
                for note in self.elf_notes:
                    row = [
                        self.sha256,
                        self.md5,
                        self.sha1,
                        note.note_name,
                        note.note_type,
                        note.note_type_str,
                        note.note_desc,
                        note.note_section,
                        current_time
                    ]
                    data.append(row)

                column_names = [
                    'sha256', 'md5', 'sha1',
                    'note_name', 'note_type', 'note_type_str',
                    'note_desc', 'note_section',
                    'analysis_date'
                ]

                if not data:
                    return None

                column_type_names = [
                    'FixedString(64)', 'FixedString(32)', 'FixedString(40)',
                    'LowCardinality(String)', 'UInt32', 'LowCardinality(String)',
                    'String CODEC(ZSTD(3))', 'LowCardinality(String)',
                    'DateTime64(3, \'UTC\')'
                ]

                return (data, column_names, column_type_names)

            except Exception as e:
                self.log.error(f"Error preparing export data: {e}")
                raise

    def get_clickhouse_table(self) -> str:
        return "redb_elf_notes"